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Job Description Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. As a Machine Learning Research Scientist, Interpretability, you'll work alongside our founders and team members to develop AI systems capable of processing and reasoning across multiple biological data modalities simultaneously. * You will develop specialized methods for understanding our biological reasoning models, reverse-engineering how they represent and process complex biological information. * You will design and conduct experiments to uncover interpretable features across biological scales. * You will address unique challenges in biological model interpretation, such as disentangling the multi-scale, hierarchical representations of biological systems * You will build biology-specific visualization tools that can map model activations to meaningful biological concepts. Who We're Looking For: * You have a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a relevant technical field. * You have a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. * You have a strong publication record in top-tier AI conferences or journals (e.g., NeurIPS, ICML, ICLR). * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX). Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges. * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and taking pride in solving them. * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty. * You have excellent communication skills and can clearly articulate complex technical concepts. * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity. Bonus points: * You have experience applying machine learning to biological or chemical problems. * You have knowledge of physics, molecular biology, chemistry, computational biology, bioinformatics, cheminformatics, or related fields. * You have experience with multi-modal learning. * You have contributed to open-source machine learning projects/ * You have experience in developing efficient code in C/C++. Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $120K - $250K

Job Description About impact.com impact.com is the world's leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L'Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results. Your Role at impact.com: We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics. This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business. You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both. What You'll Do: Yield Optimization & Pricing Models • Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory., • Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health., • Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns., • Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives., • Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions., • Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving., • Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes., • Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making., • Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers., • Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic., • Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue., • Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy., • Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate., • Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides., • Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly., • Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse. Required • Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems)., • Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack., • Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership., • Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems., • Technical skills:, • Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks)., • Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference)., • Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining., • Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events., • Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques)., • Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums., • Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms., • Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML., • Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems., • Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions., • Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling)., • Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training., • Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts., • Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack., • Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain., • Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal., • Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking., • Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project. *This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Benefits and Perks: At impact.com, we believe that when you're happy and fulfilled, you do your best work. That's why we've built a benefits package that supports your well-being, growth, and work-life balance. • Medical, Dental, and Vision insurance, • Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled, • Flexible spending accounts and 401(k), • Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life., • Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health., • A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval., • Investing in Your Growth: We're committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses., • Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver. #LI_NewYork_NewYork

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Data Science Experts Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities • Guide research and engineering teams on data science methodology, statistical inference, and modeling best practices., • Design challenging data science tasks and write accurate, well-structured analytical solutions., • Evaluate data science tasks and solutions produced by AI systems and other experts; provide clear written technical feedback to improve correctness and rigor., • Develop guidelines and evaluation frameworks to assess the quality of statistical reasoning, ML pipeline design, and data analysis approaches. Must-Have • 3+ years of professional or research experience in data science, data analysis, statistical modeling, or applied machine learning., • Ability to commit to 40 hours per week during weekdays for the duration of the engagement., • Prior experience with data annotation, labeling, evaluation, or human feedback collection., • Upload resume, • AI interview based on your resume #hiringmercor

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Data Science Experts Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities • Guide research and engineering teams on data science methodology, statistical inference, and modeling best practices., • Design challenging data science tasks and write accurate, well-structured analytical solutions., • Evaluate data science tasks and solutions produced by AI systems and other experts; provide clear written technical feedback to improve correctness and rigor., • Develop guidelines and evaluation frameworks to assess the quality of statistical reasoning, ML pipeline design, and data analysis approaches. Must-Have • 3+ years of professional or research experience in data science, data analysis, statistical modeling, or applied machine learning., • Ability to commit to 40 hours per week during weekdays for the duration of the engagement., • Prior experience with data annotation, labeling, evaluation, or human feedback collection., • Upload resume, • AI interview based on your resume

Job DescriptionJob Title: Chemistry Lab Supervisor (Full-Time) Location: New York, NY Schedule: Monday–Friday | 9:00 AM – 5:00 PM Employment Type: Full-Time Job Summary We are seeking an experienced Chemistry Lab Supervisor to oversee laboratory operations, ensure regulatory compliance, and maintain high-quality testing standards. This role involves supervising personnel, managing quality assurance processes, and supporting efficient laboratory workflow while ensuring patient safety and accurate test results. Responsibilities Laboratory Operations & Supervision • Supervise testing personnel and ensure adherence to performance standards, • Monitor quality control, instrument maintenance, and laboratory procedures, • Ensure staff are properly trained, competent, and compliant with testing protocols, • Ensure compliance with SOPs, regulatory standards, and safety protocols, • Initiate corrective actions when test performance deviates from standards, • Review and monitor proficiency testing and quality assurance activities, • Perform and oversee laboratory testing as needed, • Ensure accuracy and reliability of test results before reporting, • Monitor instrument calibration, maintenance, and validation processes, • Train, mentor, and evaluate laboratory staff, • Conduct competency assessments and performance reviews, • Assist in hiring and onboarding new team members, • Manage inventory, supplies, and equipment usage, • Ensure proper specimen handling and tracking, • Maintain a safe and compliant laboratory environment, • Communicate effectively across shifts to ensure continuity of operationsRequired Qualifications, • Bachelor’s degree in Chemistry, Biology, Medical Laboratory Science, or related field, • Minimum 4+ years of clinical laboratory experience, • Valid New York State Clinical Laboratory Technologist License (NYSED), • Strong knowledge of laboratory regulations, QA/QC processes, and compliance standards, • Experience in supervising or leading laboratory staffPreferred Qualifications, • Certification as a Medical Laboratory Scientist (MLS) (ASCP preferred), • Prior experience in laboratory leadership or supervisory role About Navitas Healthcare, LLC: It is a certified WBENC and one of the fastest-growing healthcare staffing firms in the US providing Medical, Clinical and Non-Clinical services to numerous hospitals. We offer the most competitive pay for every position we cater. We understand this is a partnership. You will not be blindsided and your salary will be discussed upfront.

Job DescriptionWhy Charlie Health? Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they're met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported. Charlie Health exists to change that. Our mission is to connect the world to life-saving behavioral health treatment. We deliver personalized, virtual care rooted in connection—between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we're expanding access to meaningful care and driving better outcomes from the comfort of home. As a rapidly growing organization, we're reaching more communities every day and building a team that's redefining what behavioral health treatment can look like. If you're ready to use your skills to drive lasting change and help more people access the care they deserve, we'd love to meet you. About the Role As a Staff Data Scientist - Growth and Marketing, you'll be seen as a thought leader among Growth, Marketing, and Revenue partners to help them be rigorous and thoughtful on how to best use data. You will bring an experienced perspective among the team to inform their roadmaps, shape their thinking, and drive outcomes. You will contribute directly to the growth of the company, via streamlining marketing measurement and approaches, leveraging statistical rigor via modelling & causal inference to teams, and via identifying new opportunities for continued and sustained impact across the org. We're a team of passionate, forward-thinking professionals eager to take on the challenge of the mental health crisis and play a formative role in providing life-saving solutions. If you're inspired by our mission and energized by the opportunity to increase access to mental healthcare and impact millions of lives in a profound way, apply today. Responsibilities • Partner with Growth, Marketing, Revenue, and Operations to turn ambiguous business questions into clear analytical recommendations that influence strategy and decision-making, • Build and iterate on lead, account, and ICP scoring models that help reps prioritize efforts and partner with Ops on data-driven territory design, • Develop models to analyze successful high-performer rep patterns to optimize onboarding and productivity, • Architect and maintain a trusted marketing measurement framework (e.g. MMM, incrementality testing [geo tests, holdouts, lift studies]), & align on consistent metric definitions (e.g. CAC, conversion, retention), • Develop spend optimization & channel allocation frameworks that account for saturation, diminishing returns, and the tradeoff between short-term acquisition and long-term outcomes, • Apply causal inference methods (DiD, synthetic controls, quasi-experiments) to own channel-level incrementality measurement, with clear decision rules & guardrails for each approach, • Design and scale repeatable experimentation frameworks for channel, creative, and audience testing, increasing velocity without compromising rigorRequirements, • 7+ years in data science/analytics roles, at least 3 of those years with Marketing, Sales, and/or Revenue teams, • Demonstrated ability to navigate an ambiguous data environment, with start-up experience preferred related questions and provide approaches with appropriate statistical rigor to a wide variety of stakeholders, • Familiarity with CRMs (e.g. Salesforce), Marketing Platforms, and the metrics / terminology associated with them (CAC, Opps, etc.), • Experience with modeling work that spans at least some of: MMM, LTV, Lead Scoring, Attribution Modeling, and Segmentation, • Strong technical proficiency: SQL, Python or R, modern ELT/ETL, OLAP databases (e.g., Snowflake), dbt, BI tools (e.g., Tableau, Hex), and experience setting up and scaling experimentation programs (A/B tests, causal inference, lift measurement), • Excellent ability to communicate, collaborate, and influence business partners at all levels, • Bonus: Healthcare Experience, Start-up Experience, • Passion for mission-driven work in mental health or healthcare settings and a desire to apply your skills to improve outcomes, • Please note: candidates located within a 75-minute commute of our NYC office are expected to work onsite 4 days/weekBenefits Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here. Additional Information The total target base compensation for this role will be between $190,000 and $270,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits. #LI-hybrid Our Values • Connection: Care deeply & inspire hope., • Congruence: Stay curious & heed the evidence., • Commitment: Act with urgency & don't give up. Please do not call our public clinical admissions line in regard to this or any other job posting. Please be cautious of potential recruitment fraud. If you are interested in exploring opportunities at Charlie Health, please go directly to our Careers Page: . Charlie Health will never ask you to pay a fee or download software as part of the interview process with our company. In addition, Charlie Health will not ask for your personal banking information until you have signed an offer of employment and completed onboarding paperwork that is provided by our People Operations team. All communications with Charlie Health Talent and People Operations professionals will only be sent from @charliehealth.com email addresses. Legitimate emails will never originate from gmail.com, yahoo.com, or other commercial email services. Recruiting agencies, please do not submit unsolicited referrals for this or any open role. We have a roster of agencies with whom we partner, and we will not pay any fee associated with unsolicited referrals. At Charlie Health, we value being an Equal Opportunity Employer. We strive to cultivate an environment where individuals can be their authentic selves. Being an Equal Opportunity Employer means every member of our team feels as though they are supported and belong. We value diverse perspectives to help us provide essential mental health and substance use disorder treatments to all young people. Charlie Health applicants are assessed solely on their qualifications for the role, without regard to disability or need for accommodation. By clicking "Submit application" below, you agree to Charlie Health's Privacy Policy and Terms of Service. By submitting your application, you agree to receive SMS messages from Charlie Health regarding your application. Message and data rates may apply. Message frequency varies. You can reply STOP to opt out at any time. For help, reply HELP.

Job Description About the Role: The Medical Technologist plays a critical role in the healthcare system by performing complex laboratory tests that aid in the diagnosis, treatment, and prevention of diseases. This position requires meticulous attention to detail to ensure the accuracy and reliability of test results, which directly impact patient care decisions. The Medical Technologist operates and maintains sophisticated laboratory equipment, analyzes biological specimens, and interprets data to provide actionable insights to physicians and healthcare providers. Collaboration with clinical staff and adherence to regulatory standards are essential to maintain laboratory quality and safety. Ultimately, this role contributes to improving patient outcomes through precise laboratory diagnostics and continuous quality improvement initiatives. Minimum Qualifications: • Bachelor’s degree in Medical Technology, Clinical Laboratory Science, or a related field from an accredited institution., • Certification as a Medical Technologist (MT) or Clinical Laboratory Scientist (CLS) by a recognized certifying body such as ASCP or AMT., • At least one year of experience working in a clinical laboratory setting performing diagnostic testing., • Strong knowledge of laboratory safety protocols and regulatory compliance requirements., • Advanced certification or specialization in areas such as microbiology, hematology, or molecular diagnostics., • Experience with laboratory information systems (LIS) and electronic medical records (EMR) integration., • Familiarity with quality management systems and participation in proficiency testing programs., • Previous experience working in a hospital or high-volume clinical laboratory environment., • Perform routine and specialized laboratory tests on blood, tissue, and other body fluids using automated and manual techniques., • Operate, calibrate, and maintain laboratory instruments and equipment to ensure optimal performance and compliance with safety standards., • Analyze test results, identify abnormalities, and report findings accurately and promptly to healthcare providers., • Maintain detailed records of tests performed, quality control procedures, and equipment maintenance logs., • Collaborate with medical staff to troubleshoot technical issues and provide expert guidance on laboratory procedures., • Ensure compliance with all regulatory requirements, including OSHA, CLIA, and CAP standards. The Medical Technologist utilizes strong analytical skills daily to conduct and interpret a wide range of laboratory tests accurately. Attention to detail is critical when calibrating instruments and reviewing test results to ensure data integrity and patient safety. Effective communication skills are essential for collaborating with healthcare professionals and documenting findings clearly. Technical proficiency with laboratory equipment and software systems supports efficient workflow and compliance with regulatory standards. Additionally, problem-solving skills enable the technologist to troubleshoot equipment issues and optimize laboratory processes for improved diagnostic outcomes. Evening/Overnight Tuesday-Saturday 8 hours/80 hours

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Environmental Science Expert Type: Contract Compensation: $50–$70/hour Location: Remote Role Responsibilities • Build a realistic digital workspace centered on the Drive folders you use daily. Include site assessment reports, permit applications, monitoring data summaries, and more. Represent platforms like Esri ArcGIS, SAS, MATLAB, and Socrata., • Design multi-step tasks grounded in your real workflows. Require navigating multiple apps, files, and stakeholders to challenge frontier AI agents., • Collaborate with other environmental-science experts to design the environment, shape task scope, and review scenarios for realism and rigor., • Work asynchronously with research teams to refine task designs and evaluation criteria for environmental-science agent benchmarks. Must-Have • 3+ years of full-time experience at a federal/state environmental agency, major environmental consulting firm, F500 sustainability team, or R1 university., • Background in environmental assessment and compliance, air, water, or waste permitting and monitoring, contaminated-site investigation/remediation, corporate sustainability, ESG reporting, or climate-risk analysis., • Day-to-day use of Esri ArcGIS, Google Maps Platform, SAS, MATLAB, and Socrata., • Upload resume, • AI interview based on your resume

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Environmental Science Expert Type: Contract Compensation: $50–$70/hour Location: Remote Role Responsibilities • Build a realistic digital workspace centered on the Drive folders you use daily. Include site assessment reports, permit applications, monitoring data summaries, and more. Represent platforms like Esri ArcGIS, SAS, MATLAB, and Socrata., • Design multi-step tasks grounded in your real workflows. Require navigating multiple apps, files, and stakeholders to challenge frontier AI agents., • Collaborate with other environmental-science experts to design the environment, shape task scope, and review scenarios for realism and rigor., • Work asynchronously with research teams to refine task designs and evaluation criteria for environmental-science agent benchmarks. Must-Have • 3+ years of full-time experience at a federal/state environmental agency, major environmental consulting firm, F500 sustainability team, or R1 university., • Background in environmental assessment and compliance, air, water, or waste permitting and monitoring, contaminated-site investigation/remediation, corporate sustainability, ESG reporting, or climate-risk analysis., • Day-to-day use of Esri ArcGIS, Google Maps Platform, SAS, MATLAB, and Socrata., • Upload resume, • AI interview based on your resume

Job DescriptionAbout CookUnity: Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry's best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul. Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world. If that mission has you hungry in more ways than one, you've found the right job posting. About the Role We're hiring for an experienced ML-focused Data Scientist to own growth-oriented modeling across the customer lifecycle - acquisition, activation, retention, resurrection and monetization. You'll work alongside other data scientist to design, validate, and productionize statistical and ML systems (pLTV, churn/survival, uplift/incrementality, lookalikes, clustering/embeddings, NBA/ranking) that directly drive growth. This is a hands-on role for someone with strong mathematical/statistical foundations, broad modeling experience, and pragmatic MLOps chops who can lead experiments and partner closely with Marketing, Engineering, CRM, and Product. What you'll do… • Lifecycle modeling: Build and maintain predictive LTV, churn (including survival/time-to-event), order-rate, and resurrection models that feed acquisition, CRM, and retention strategies., • Acquisition & lookalikes: Create lookalike / propensity models for paid channels and audience construction; optimize CAC vs LTV tradeoffs., • Next-Best-Action & personalization: Develop NBA/ranking models, small-scale recommenders and embedding-based similarity systems to increase activation and orders., • Unsupervised & representation learning: Lead segmentation, clustering, embeddings and representation work that create actionable cohorts and features., • Production & MLOps: Own the full model lifecycle - training pipelines, CI/CD, model registries, containerized deployment, monitoring, retraining and drift detection; partner with engineers to operationalize models into CRM, marketplace and paid channels., • Model governance & reproducibility: Ensure models are well-tested, explainable, calibrated, and auditable; document assumptions, limitations and business mappings., • Cross-functional influence: Translate technical work into product recommendations, dashboards and clear narratives for Growth, Marketing and Engineering. Mentor peers and raise modeling and MLOps standards.Required qualifications, • 5-8+ years in data science, applied ML or statistics, with a track record of shipping production models., • Strong math & statistics: probability, inference, regression, survival analysis/time-to-event, causal reasoning, and familiarity with statistical modeling tradeoffs., • End-to-end ML experience: experience building, validating and deploying classification/regression/ensemble/deep models; comfort with embeddings and representation learning., • MLOps & production skills: pragmatic experience with model CI/CD, model registries (MLFlow or similar), containerization (Docker), orchestration (Airflow), and runtime infra (K8s / ECS)., • Software engineering & tooling: Python (pandas, scikit-learn, XGBoost/LightGBM, PyTorch/TensorFlow optional), strong code hygiene, testing and reproducibility., • Product & stakeholder collaboration: excellent communication, ability to embed with Growth/CRM/Marketing and translate models into product decisions., • Education: BS in a quantitative field required; MS/PhD in statistics, math, CS, economics or similar preferred.Nice-to-haves, • Experience in subscription marketplaces, food-tech, or consumer marketplaces., • Familiarity with feature stores, Snowflake/BigQuery, and production monitoring tools., • Experience with causal libraries (EconML), uplift frameworks, or survival modeling packages., • Prior work on small-scale recommender systems, embeddings, or NLP personalization. Learn More About CookUnity We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles – The values and behaviors that guide how we operate, collaborate, and scale. We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect! Benefits 🩺 Health Insurance coverage 🌅 401k Plan ⛱ Unlimited PTO 🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical 🐣 Paid Family leave 🕯 Compassionate Leave: 3-5 days each time the need arises 🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly 🧘🏽️‍♀️ Wellness perks: access to a nutritional coach and fitness subsidies to build a healthy lifestyle 👩🏾️‍🏫 Personalized Spanish coach 🌟 Awesome opportunity to join a company that is looking to change how we eat and how chefs work! Compensation All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.Pay Range for this position$160,000—$185,000 USD If you're interested in this role, please submit your application, and if we think you might be a fit, we'll get in touch with you. Thank you for your time! CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability. A quick note for all candidates We've recently seen an increase in recruitment scams across the industry, and we want to make sure you (and your data) stay safe while applying to CookUnity. We also want you to know that we take this seriously — sometimes, as part of our process, we may ask for a brief "proof of humanity" to confirm that we're connecting with a real person, not an impersonator. Here are a few tips to help you protect yourself and know what to expect from us: • Apply only through our official channels. All open roles are listed on our official careers page: careers.cookunity.com, • Our recruiters are real people — and easy to verify. You can always find them on LinkedIn with verified profiles. If you're unsure, feel free to reach out to us on our official LinkedIn Company Page., • We only communicate through official CookUnity channels. That means emails ending in @cookunity.com and interviews held through official company platforms (Google Meet or Zoom) — never WhatsApp, Telegram, or SMS.

Job Description Maven is the world's largest virtual clinic for women and families on a mission to make healthcare work for all of us. Maven's award-winning digital programs provide clinical, emotional, and financial support all in one platform, spanning fertility & family building, maternity & newborn care, parenting & pediatrics, and menopause & midlife. More than 2,000 employers and health plans trust Maven's end-to-end platform to improve clinical outcomes, reduce healthcare costs, and provide equity in benefits programs. Recognized for innovation and industry leadership, Maven has been named to the Time 100 Most Influential Companies, CNBC Disruptor 50, Fast Company Most Innovative Companies, and FORTUNE Best Places to Work. Founded in 2014 by CEO Kate Ryder, Maven has raised more than $425 million in funding from top healthcare and technology investors including General Catalyst, Sequoia, Dragoneer Investment Group, Oak HC/FT, StepStone Group, Icon Ventures, and Lux Capital. To learn more about Maven, visit us at mavenclinic.com. An award-winning culture working towards an important mission – Maven Clinic is a recipient of over 30 workplace and innovation awards, including: • Fortune Change the World (2024), • CNBC Disruptor 50 List (2022, 2023, 2024), • Fortune Best Workplaces for Millennials (2024), • Fortune Best Workplaces in Health Care (2024), • TIME 100 Most Influential Companies (2023), • Fast Company Most Innovative Companies (2020, 2023), • Built In Best Places to Work (2023), • Fortune Best Workplaces NY (2020, 2021, 2022, 2023, 2024), • Great Place to Work certified (2020, 2021, 2022, 2023, 2024), • Fast Company Best Workplaces for Innovators (2022), • Design, build, and deploy end-to-end AI-powered solutions using AI models (e.g., OpenAI, Gemini) and modern orchestration techniques such as RAG, multi-call prompting, and agent frameworks to power intelligent product experiences., • Work with product, data, and engineering teams to turn rich healthcare data into actionable insights and intelligent workflows that improve the care journey for both members and providers., • Develop robust ML pipelines and platform components that enable model experimentation, fine-tuning, training from scratch when needed, and deployment in production environments — with a strong focus on scalability, safety, and performance., • Collaborate cross-functionally to prototype and productionize AI-driven features such as personalization, care routing, decision support, and summarization., • Drive architecture discussions and technical decision-making across AI/ML systems, promoting best practices in coding, design, and evaluation of AI models., • Mentor engineers and data scientists across the organization, fostering a strong culture of curiosity, experimentation, and AI fluency., • A strong track record in either:, • Building AI-powered applications using foundation models and orchestration techniques (e.g., RAG, agents, LangChain, vector search), or, • Deep experience as a data scientist working across the data science lifecycle — from understanding messy, complex datasets to training or fine-tuning models that deliver measurable business impact., • Experience integrating and deploying foundation models via platforms like OpenAI, Google Vertex AI, or similar., • A clear understanding of how to work with health-related datasets, including user behavior, care journeys, health profiles, and provider interactions., • Fluency in Python and experience with backend or platform engineering in one or more additional languages (Go, Java, etc.)., • Familiarity with cloud-native systems (e.g., containerization, orchestration, distributed systems) and how to operationalize AI solutions within them., • Experience with data preprocessing, feature engineering, model evaluation, and end-to-end ML deployment workflows., • A collaborative mindset, strong communication skills, and a passion for using AI to improve healthcare outcomes., • Bachelor's or Master's degree in Computer Science or related field, or equivalent experience. Maven embraces a flexible hybrid work model. Our teams primarily operate from the New York Metropolitan area, NY, San Francisco/Bay Area, CA, Seattle, WA, Boston, MA, Chicago, IL, and Washington, D.C. For those in our New York City office, we encourage in-person collaboration by requiring team members to work onsite three days a week (Tuesday, Wednesday, Thursday). For those based in San Francisco/Bay Area, CA, Seattle, WA, Boston, MA, Chicago, IL, and Washington, D.C., we encourage in-person collaboration by requiring team members to attend quarterly Work Together Days within these cities. This policy aims to balance remote work flexibility with the benefits of face-to-face interaction. At Maven we believe that a diverse set of backgrounds and experiences enrich our teams and allow us to achieve above and beyond our goals. If you do not have experience in all of the areas detailed above, we hope that you will share your unique background with us in your application and how it can be additive to our teams. Benefits That Work For You Our benefits are designed to support your health, well-being and career development, helping you thrive both personally and professionally. We remain focused on providing a competitive benefits package for our employees. On top of standards such as employer-covered health, dental, and insurance plan options, we offer an inclusive approach to benefits: • Maven for Mavens: access to the full platform and specialists, including care for mental health, reproductive health, family planning and pediatrics., • Whole-self care through wellness partnerships, • Hybrid work, in office meals, and work together days, • 16 weeks 100% paid parental leave and new parent stipend (for Mavens who've been with us for 1 year+), • Annual professional development stipend and access to a personal career coach through Maven for Mavens Maven is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. Maven is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Maven Clinic interview requests and job offers only originate from an @mavenclinic.com email address (e.g ). Maven Clinic will never ask for sensitive information to be delivered over email or phone. If you receive a scam issue or a security issue involving Maven Clinic please notify us at: . For general and additional inquiries, please contact us at .

Job Description About Synaptrix Labs Inc. Synaptrix is on a mission to revolutionize brain-computer interfaces through non-invasive approaches. We believe that the power to diagnose and treat neurological conditions safely, and to expand human potential, will become a reality with the right fusion of deep learning, signal processing, and computational neuroscience. We're seeking a full time Research Scientist, Artificial Intelligence (PhD) to join our growing team of researchers & engineers. If you're passionate about shaping the future of brain-computer interfaces and excited by the potential of deep learning in neurotechnology, we want to hear from you! Responsibilities: • Design, prototype, and optimize state-of-the-art AI systems for neural decoding, including diffusion models, graph neural networks, contrastive/self-supervised frameworks, and transformer-based sequence models., • Conduct foundational research on neural time-series representation learning: build architectures that extract latent dynamics from EEG, EMG, or related biosignals., • Develop high-fidelity simulation environments for testing decoding algorithms, incorporating stochastic signal noise and realistic biophysical constraints., • Scale model training across multi-GPU and multi-node clusters using PyTorch Distributed, DeepSpeed, or JAX/Flax; profile and tune system performance for sub-10 ms inference latency., • Build and maintain end-to-end research pipelines for large-scale signal datasets, including preprocessing, artifact rejection, and multimodal fusion with video, audio, and IMU data., • Collaborate with neuroscientists and hardware engineers to integrate learned models into real-time BCI control loops and embedded systems., • Contribute to core ML infrastructure: experiment tracking, model versioning, dataset lineage, and reproducibility standards., • PhD or equivalent deep technical expertise in Machine Learning, Artificial Intelligence, Computer Science, Computational Neuroscience, or related fields., • Strong command of PyTorch or JAX, with experience implementing custom training loops, loss functions, and model architectures., • Proven ability to conduct end-to-end research, from conceptual design to reproducible experiments and evaluation., • Strong mathematical foundations in linear algebra, probability, optimization, and information theory., • Experience working with high-dimensional time-series or sensory data (EEG, speech, video, motion capture, etc.)., • Skilled in Python, NumPy, Pandas, and scientific computing workflows; experience with CUDA or low-level GPU debugging is highly valued., • Deep familiarity with neural signal modeling, neural decoding, or biosignal preprocessing (EEG/MEG/ECoG/EMG)., • Experience designing self-supervised or generative models (diffusion, VAEs, contrastive, masked modeling) for noisy, non-stationary data., • Background in reinforcement learning, optimal control, or human-in-the-loop systems, especially in continuous domains., • Publications or preprints in top venues (NeurIPS, ICML, ICLR, CVPR, EMBC, Nature Neuro)., • Familiarity with distributed training, mixed-precision, multi-GPU orchestration, and cloud ML infrastructure (AWS/GCP/Azure)., • Contributions to open-source ML frameworks or custom CUDA kernels., • Understanding of neural signal acquisition hardware, embedded inference, or edge ML deployment. At Synaptrix Labs, we celebrate curiosity, open collaboration, and scientific rigor. Our interdisciplinary team spans neuroscience, AI, and clinical research, and we are united by the belief that non-invasive BCI is the key to unlocking a new era in healthcare, accessibility, and human augmentation. Expected Compensation: The base salary for this role is anticipated to fall within the following range. Actual compensation will depend on your experience, technical expertise, and relevant education or training. In addition to base pay, Synaptrix offers equity to all full-time employees, reflecting our commitment to shared success and long-term company growth. Base Salary Range: $85,000 - $150,000 USD What We Offer: • An opportunity to change the world and work with some of the smartest and most talented experts from different fields, • Growth potential; we rapidly advance team members who have an outsized impact, • Paid holidays, unlimited PTO

Job DescriptionOur Company Arch is a Series B financial technology company that automates the management of private investments, improving access, understanding, and the human experience of investing across asset classes. Private investments such as venture capital, hedge funds, and private equity, make up roughly 25% of the investment universe. Traditionally, investors, advisors, banks, families, and managers track hundreds of investments in complicated spreadsheets, file folders, and busy inboxes. Not only is this tedious and time-consuming, but it is rife with opportunity for manual data entry errors, inconsistent reporting, and lost information. Enter, Arch. Arch delivers standardized data, documents, and insights in a single platform, avoiding the need to chase information across dozens or hundreds of ‘portals’. Our purpose is to save investors’ time while empowering them to make more informed investment decisions, leading to better financial outcomes. We are a fast-growing, dynamic team of 200+, serving over 400 clients, including several of America’s largest banks, families, and financial institutions. We’ve over doubled the size of the company every year since inception and we are looking to hire in all departments as we scale. About the Role We are looking to hire a Senior Manager, Data Operations to lead and scale the data services function within Arch's data organization. In this role, you will lead a team responsible for extracting, analyzing, and delivering data from Arch's platform for business use. You'll formalize processes, establish operational cadences, and build the foundation for a scalable data services function that enables teams across the company to operate more effectively. This role is key to solving the company's most difficult operational data challenges, including problems that don't neatly fall into product or engineering and require strong business judgment to navigate. You will investigate root causes, determine whether solutions are possible, and drive the work through completion. You'll serve as a bridge between technical teams and internal stakeholders, advising on data processes and best practices while ensuring projects move forward and deliver meaningful outcomes. The ideal candidate enjoys solving complex problems, is comfortable operating in ambiguous environments, and takes full ownership of projects from initial idea through delivery. Your responsibilities will include: * Owning and scaling Arch's data services function, including the team responsible for extracting and delivering data from the platform for business use across the organization. * Leading high-impact internal data initiatives that help Arch operate more intelligently, including projecting data volume, building out dashboards, establishing regular reporting cadences, and identifying operational insights. * Driving end-to-end delivery of data projects, from identifying the problem and determining feasibility to building or coordinating the solution and ensuring successful implementation. * Partnering closely with teams across sales, operations, product, engineering, and leadership, acting as both a service organization and a thought partner on how data supports the business. * Serving internal teams as stakeholders by keeping them informed on project progress, timelines, and outcomes. * Managing the team's intake of ad hoc requests, ensuring work is triaged, actioned or escalated appropriately, and completed within SLA. * Supporting data-intensive products and processes by collaborating with clients to procure data, integrating it into the system, and validating output. * Building and scaling the data services team, including managing direct reports, hiring additional team members, and formalizing processes and documentation while maintaining continuity of existing operations. Reach out to us if you: * Have 7+ years of experience in operational or business-focused roles and are deeply curious about how companies actually operate. * Have demonstrated leadership experience, including managing direct reports, building teams, or leading cross-functional initiatives. * Have strong business sense and are an exceptional problem solver who thrives in ambiguous environments. * You don't need to be a pure data scientist or engineer, but you should have strong technical data fluency. Our core stack includes MySQL, Python, Notion, and MS Office / Google Suite. We build dashboarding and reporting tools internally. We're looking for experience with: * SQL (MySQL) or Python (one is sufficient) * Working with large datasets * Data cleaning, transformation, and analysis * Building projections or data models * Measuring and defining operational metrics * Enjoy taking end-to-end ownership of projects and driving them from kickoff through launch. * Have strong written and verbal communication skills and can clearly explain technical issues to non-technical stakeholders. * Are comfortable coordinating across teams and communicating progress clearly with stakeholders. * Thrive in fast-paced, high-stakes environments where priorities shift and new challenges arise frequently. * Are comfortable operating with urgency and delivering high-quality work on tight timelines driven by client SLAs. Bonus points if you: * Have worked with alternative investments, financial data, financial technology, or data delivery platforms. * Have experience in a data analyst, data science, or data operations role. * Have worked with large-scale or complex data systems. * Have experience building predictive models, statistical analysis, or data quality measurement frameworks. * Have experience in consulting or environments where solving open-ended problems was a core part of the role. A Note about us: Most of our full-time roles are based onsite at our New York City office, where our team thrives on in-person collaboration and dynamic teamwork. Being onsite daily enables us to build strong connections, move quickly, and deliver exceptional service to our clients. For select roles, we are also open to candidates based in Boston. If a role is open to Boston, it will be listed explicitly in the job location. We encourage applicants who are located in or open to relocating to the listed location to apply and join us in this hands-on, collaborative environment Some perks of working for Arch include: * Strong Team - You’ll be backed by a strong team that consistently exceeds client expectations and ships new products quickly. * Your work is high impact - Being part of a small team means you have real responsibility and impact from day one. You'll be involved in discussions that drive the growth and direction of our platform from the very beginning. * Product Market Fit - We have strong product market fit, exceptionally low churn, and have grown mostly organically through word of mouth. * Team community and camaraderie - We have enormous trust in each other and always do what we can do to support one another. We're always ready to step in to help. * Great office - we’ve invested in a great space for the Arch team to come together, at 18th and Park in Manhattan (the old Buzzfeed / NYT headquarters). * Lunch is on Us - Grab lunch on us while you’re in the office and take a break to laugh, brainstorm, or just hang out with your teammates over a meal. Compensation Range: $145K - $170K

Job DescriptionCareer Renew is recruiting for one of its clients a Technical Product Manager, Data and Internal Products - this is a fully remote position for US-based candidates. Salary range: 180-230K USD plus benefits plus equity.We are the leading provider of innovative identity and risk solutions, empowers institutions and individuals to transact confidently with one another by preventing synthetic fraud, identity theft, and emerging forms of first party fraud at the point of account application. Its solutions enable these secure transactions by leveraging a deep understanding of identity and risk, and are informed by machine learning models and insights from a team of top risk analysts. We proudly serve a broad array of financial institutions, from the largest U.S. banks to leading credit unions and fintech unicorns to help stop fraud at account opening and beyond. Headquartered in San Francisco, the company was founded in 2017 by Naftali Harris and Max Blumenfeld and it has raised $85M to date from investors including Andreessen Horowitz, Craft Ventures, and NYCA Partners, among others. We are looking for a Data Product Manager with 5+ years of experience to lead internal initiatives within our Tech organization. This person will build and maintain our core internal technology, spanning critical datasets, internal services, and the underlying platforms that support our products and analytics. What will you be doing? * Own the product vision, roadmap, and execution for internal technical initiatives, with a strong focus on dataintensive systems. * Lead cross-functional efforts to improve the quality, reliability, and usability of internal systems, including datasets and shared services. * Drive long-term initiatives to future-proof internal data and technology assets, ensuring they scale with evolving needs. * Partner with engineering, data science, solutions analytics, and product stakeholders to understand use cases and clarify requirements. * Manage prioritization across competing internal demands, balancing immediate impact with long-term strategic value. Key Requirements * 5+ years of experience with data-heavy or platform-oriented products, with a focus on ML/Data Science strongly preferred. * Hands-on experience working with large datasets (e.g., Spark, Databricks, BigQuery, Snowflake). * Strong understanding of big data concepts, data pipelines, data cleaning/normalization, and data modeling. * Demonstrated ability to partner effectively with engineering, data science, and analytics teams on deeply technical problems. * Experience driving large internal initiatives with multiple stakeholders and managing cross-functional dependencies. Tech stackSpark, Databricks, BigQuery, Snowflake Requirements: 5+ years of experience PM, founder, or equivalent cross-functional product role (Mandatory) Resume must show both big data product work and internal tooling experience with specific projects named (Mandatory) At least 1 year at a Series B/C startup; current or most recent role must be at a startup, not big tech (Mandatory) Prior engineering title required (SWE, data scientist, ML engineer, or highly technical data analyst) (Mandatory) Data pipeline experience required: production-level work with data ingestion, cleaning/normalization, and modeling with specific tools cited (Mandatory) Python and AWS familiarity required; big data tooling (Spark, Databricks, BigQuery, Snowflake, or Redshift) must be explicitly named on resume (Mandatory) Domain experience in fintech, payments, fraud, or identity is a significant differentiator (Nice-to-have) Located and authorized to work in the United States. (Mandatory) Why you should join Market-leading fraud prevention company - We're the go-to identity verification solution for major US banks, credit unions, and fintech unicorns, processing hundreds of millions of identities. $85M raised from top-tier investors - Backed by Andreessen Horowitz, Craft Ventures, and NYCA Partners with strong financial runway. Forbes Fintech 50 recognition - Named to the prestigious list every year since 2023, plus we made history as the first eCBSV provider. Competitive compensation package - $180K-$230K base salary plus equity and comprehensive benefits including employer-paid health insurance for you and dependents. Remote-first culture - Work from anywhere in the US with flexible PTO and regular company-wide in-person events.

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Expert Professionals — AI & Data Science Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities • Guide research and engineering teams to close knowledge gaps in AI and data science domains. Surface nuances that distinguish expert-level work from surface-level reasoning., • Design challenging agentic tasks rooted in real-world ML, data science, data engineering, and software workflows. Write accurate, well-documented solutions that serve as ground truth., • Evaluate AI agent outputs against your solutions. Provide detailed written feedback capturing correctness, efficiency, and reasoning quality., • Develop and refine evaluation frameworks and rubrics for assessing agentic behavior on AI and data science tasks. Must-Have • 3+ years of research, academic, or industry experience in Machine Learning, Data Science, Software Engineering, Computer Science, Statistics, Biology, Electrical/Mechanical/Civil Engineering, Physics, Chemistry, Mathematics, Materials Science, or other STEM background., • Demonstrated technical expertise in programming, data analysis, ML modeling, statistical methods, or computational methods., • Ability to commit to 40 hours per week during weekdays for the duration of the engagement., • Prior experience with data annotation, labeling, evaluation, or human feedback collection., • Upload resume, • AI interview based on your resume

Job Description Job Title: Senior Data Scientist Location: United States (Can be based anywhere) Travel: As needed About the Role We are looking for a Senior Data Scientist to join a high-performing analytics team working on complex, real-world problems across multiple industries. In this role, you will collaborate with cross-functional teams to design, build, and deploy advanced analytics and AI solutions that drive meaningful business impact. You'll work on a variety of projects, ranging from optimizing operations to building machine learning and AI-driven applications, while continuing to grow your technical and problem-solving skills. Key Responsibilities • Translate business problems into data-driven solutions, • Perform exploratory data analysis and identify key insights, • Build, test, and deploy machine learning and AI models, • Develop and evaluate models using statistical techniques and experimentation (including A/B testing), • Work with modern AI approaches such as large language models (LLMs) and retrieval-augmented generation (RAG) when applicable, • Deploy solutions via APIs or data pipelines and monitor performance over time, • Collaborate with engineers and product teams to integrate solutions into applications, • Ensure models are accurate, explainable, and scalable, • Python and SQL for data science and analytics, • Distributed computing tools like Spark/PySpark, • Cloud platforms such as AWS, Azure, or GCP, • Tools like Airflow, Databricks, Docker, and Kubernetes, • Bachelor's degree with 8+ years of experience, or Master's/PhD in Computer Science, Statistics, Mathematics, or a related field, • Experience applying machine learning to real-world datasets, • Strong programming skills in Python and SQL, • Experience with large-scale data processing (e.g., Spark), • Familiarity with cloud environments and modern data tools, • Strong problem-solving and analytical thinking skills, • Excellent communication skills with the ability to explain technical concepts clearly, • Exposure to a wide range of industries and use cases, • Opportunities to work on cutting-edge AI and data science projects, • A collaborative, fast-paced, and learning-focused environment, • Strong mentorship and career growth opportunities

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Data Science Experts Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities • Guide research and engineering teams on data science methodology, statistical inference, and modeling best practices., • Design challenging data science tasks and write accurate, well-structured analytical solutions., • Evaluate data science tasks and solutions produced by AI systems and other experts; provide clear written technical feedback to improve correctness and rigor., • Develop guidelines and evaluation frameworks to assess the quality of statistical reasoning, ML pipeline design, and data analysis approaches. Must-Have • 3+ years of professional or research experience in data science, data analysis, statistical modeling, or applied machine learning., • Ability to commit to 40 hours per week during weekdays for the duration of the engagement., • Prior experience with data annotation, labeling, evaluation, or human feedback collection., • Upload resume, • AI interview based on your resume

Job Description Hi, we're Oscar. We're hiring an Applied AI Engineer to join our AI team. Oscar is the first health insurance company built around a full stack technology platform and a focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family. About the role Join Oscar's AI team to build and launch transformative AI-powered products that redefine the healthcare experience for millions. As an Applied AI Engineer, you'll take end-to-end ownership of high-impact projects—conceiving, prototyping, and deploying generative AI solutions that solve real-world problems across the healthcare ecosystem.You'll work alongside a world-class team of engineers and data scientists, rapidly iterating on ideas and shipping production-ready applications that drive measurable business and user outcomes. You'll have the autonomy to identify opportunities, experiment with the latest AI models and techniques, and deliver solutions that streamline operations, improve patient experiences, and move the needle for Oscar and our members. You will report to the Sr. Director, AI. Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid Pay Transparency: The base pay for this role is: $163,944 - $236,911 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses. Responsibilities • Lead the design, development, and deployment of AI-driven products and features, from zero-to-one prototypes to robust production systems., • Collaborate cross-functionally with product, design, and business teams to deeply understand user needs and deliver solutions that move key metrics., • Rapidly experiment with new models, techniques, and tools (including LLMs, RAG, and agentic workflows), iterating based on data and user feedback., • Build and scale full-stack applications and intelligent agents that automate complex healthcare workflows and deliver seamless user experiences., • Stay on the cutting edge of the AI ecosystem, evaluating and integrating emerging technologies to keep Oscar at the forefront of healthcare innovation., • Contribute to Oscar's AI strategy and technical vision, helping shape the future of healthcare through technology., • Other duties as assignedQualifications, • 7+ years of professional experience in software engineering, data science, or a related field, with a track record of impactful accomplishments, • Strong Python programming skills, • Experience solving complex, ambiguous problems, • Experience designing and analyzing experiments or evaluations, • Experience or an interest in prototyping full-stack applicationsBonus Points, • Experience with the healthcare industry. Familiarity with claims or clinical data., • Degree in math, statistics, data science, or engineering., • Our ideal candidate is a data scientist with an engineering background, an engineer with a data science background, or a founder-type who combines product thinking, rapid prototyping, and hands-on coding to deliver real-world impact., • Experience with NLP, neural networks, transformers, and modern AI frameworks., • Knowledge of containerization and deployment tools (e.g., Docker, Kubernetes) or full-stack development (e.g., React, Golang)., • Experimental mindset: comfort with testing hypotheses and iterating on failures. This is an authentic Oscar Health job opportunity. Learn more about how you can safeguard yourself from recruitment fraud here. At Oscar, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change health care -- an experience made whole by our unique backgrounds and perspectives. Pay Transparency: Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. Full-time employees are eligible for benefits including: medical, dental, and vision benefits, 11 paid holidays, paid sick time, paid parental leave, 401(k) plan participation, life and disability insurance, and paid wellness time and reimbursements. Artificial Intelligence (AI): Our AI Guidelines outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts. Reasonable Accommodation: Oscar applicants are considered solely based on their qualifications, without regard to applicant's disability or need for accommodation. Any Oscar applicant who requires reasonable accommodations during the application process should contact the Oscar Benefits Team () to make the need for an accommodation known. California Residents: For information about our collection, use, and disclosure of applicants' personal information as well as applicants' rights over their personal information, please see our Privacy Policy.

Job Description eDNA Post-Doctoral Associate OceanX About OceanX: OceanX is a nonprofit working to unlock the ocean's sustainable potential. Through a dual focus on science and education, we're building a new paradigm where humanity and the ocean mutually thrive. Our approach is fueled by exploration, leveraging advanced research, multimedia educational programs, cross-sector partnerships, and advanced technology to help transform how people understand and value the ocean. Our work strives to fortify biodiversity and increase the sustainable use of ocean resources to help ensure the ocean remains a foundation for human wellbeing and potential. OceanX is a nonprofit operating program of Dalio Philanthropies. For more information, visit and follow OceanX on Facebook, Instagram, Twitter, X, and LinkedIn. Position Summary: OceanX is seeking a post-doctoral associate in the field of marine eDNA and meta genomics. The position involves work in a laboratory at sea on the research vessel OceanXplorer. The position would require performing nucleic acid sequencing and genome assembly from samples (water, soil, organisms, etc.) collected at sea during international expeditions. When not working on the vessel, the position would entail data analysis at home, in a New York City office or at a collaborating laboratory, domestically or abroad. Experience in marine eDNA purification and analysis, genome assembly and analysis are required. Ability to work independently and with international scientists aboard a research vessel is a must. The position comes with unique access to a range of exploration opportunities aboard an advanced research vessel including submersibles, ROVs, CTDs and a SCUBA diving platform. It is expected that the scientist would develop, execute and publish their scientific work in leading, peer-reviewed scientific journals. OceanX is an entrepreneurial environment which values team players who can manage priorities and workstreams simultaneously. To thrive and succeed within our unique culture and work environment, you must demonstrate humility, innate curiosity, and openness to new ideas/approaches. You also must be hard working, composed and goal oriented. Everyone working with OceanX is expected to be honest, open to giving and receiving objective feedback, constantly striving for self-improvement, and committed to the pursuit of excellence. Position Type: • This is a two-year contract position, with the possibility of renewal after the two-year term, • While the role will work closely with the OceanX team in support of OceanX initiatives, it will be formally employed and managed by a third-party staffing partner, • Note: This position requires spending approximately 50% of working time aboard the vessel, • Develop scientific projects within the field of environmental DNA in the marine environment in collaboration with the OceanX Science Program Director and Vice-Chair/Chief Science Officer, • Collect and analyze samples and data at-sea under scope of mission and projects as-developed with Science Program Director, • Utilize laboratory facilities and equipment on board the OceanXplorer, maintain an inventory of consumables required and/or used to execute project objectives, • Collaborate on board OceanXplorer with guest scientific teams and ship-based teams (ROV, Sub, Science) as-directed by the Science Program Officer to achieve project sampling goals and data requirements, • Professional Experience:, • PhD in molecular biology and genomics, • Ability to work and thrive in an entrepreneurial, rapidly evolving environment, with significant ambiguity, • Ability to communicate effectively in written and oral communications, • Strong project management capabilities, • Proven track record of taking initiative, with the ability to multi-task, collaborate with various team members, and conduct oneself in a highly professional manner when working with both internal and external colleagues., • Personal Attributes:, • Determined, resourceful and practical. An independent, self-starter, with a "roll up your sleeves" attitude and strong work ethic, • Agility, with a track record of getting things done, • Organized, reliable, and meticulous, • Ability to prioritize, meet tight deadlines, anticipate needs, and maintain high quality work, • Strong interpersonal and communication skills (written and verbal), • Comfortable with ambiguity, • Maintains high standards, • Highly collaborative, • General curiosity and passion for the Ocean, • Other Requirements:, • Must be willing and able to live and work aboard the OceanXplorer for prolonged deployments at sea Compensation: Compensation for this role is in the range of USD $90,000–$100,000.

Job Description Does getting in on the ground floor as an initial stakeholder, building out your own team, and building a solution that has never been built before, get you excited? Do you want to be the person, when people are talking about some awesome innovation in awe, to be able to proudly say you were instrumental in building it? If so then this could be an exciting opportunity for you. My client partners with companies ranging from fortune 500 to start-ups across all industries to solve their most complicated problems. The main one, most are wrestling with is how to use data and research for their decisions. With this hole in the market in mind, they have recently brought over one of the brightest minds from the AI/Machine learning world to build a product that doesn’t exist at this moment. It is tremendously ambitious goal, and they need a special team to do it. They are constructing its own floor, in their current space, and it is just at the start of this exciting journey. They are building a tool that can automate and replace the hundreds of thousands to million dollars that companies are spending in data science. This tool will greatly cut down on in some cases eliminate the need for companies to pour over data researching to find trends, it will do it for them, basically personalization for B2B. They are looking for a Senior Data Scientist to come on board and lead this ambitious initiative. If applying data mining techniques, doing statistical analysis, and building high quality prediction systems sounds like fun to you, keep reading. You will do things like , use machine learning techniques, build recommendation systems, and develop internal A/B testing procedures, and automation creation reporting. RESPONSIBILITIES · Selecting features, building and optimizing classifiers using machine learning techniques · Data mining using state-of-the-art methods · Enhancing data collection procedures to include information that is relevant for building analytic systems · Processing, cleansing, and verifying the integrity of data used for analysis · Doing ad-hoc analysis and presenting results in a clear manner · Creating automated anomaly detection systems and constant tracking of its performance · Utilize database technologies, including SQL, ETL, EMR, and Redshift to shape data and statistical modeling packages like R and python to build customer models. · Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation. · Research and implement novel machine learning and statistical approaches QUALIFICATIONS · Excellent understanding of machine learning techniques and algorithms · Experience with common data science toolkits and data visualization tools · Proficiency in using query languages such as SQL, Hive, Pig etc. · Good applied statistics skills, such as distributions, statistical testing, regression, etc. · Good scripting and programming skills such as Python · Bachelor’s degree in computer science, Engineering, Mathematics, Statistics or related fields, or equivalent practical experience. Masters is preferred · Relevant working experience in an analytical role involving data extraction, analysis, model building, deployment and communication of insights · Excellent quantitative modeling, statistical analysis skills and problem-solving skills. Sophisticated user of statistical tools. It is a truly unique work environment, where they are allowing the right candidate to be part of the creative, as well as the execution of the idea. The company empowers their employees, by choosing the right people, letting them use their unique skills, and giving them every resource, and power to make decisions. Truly a great opportunity to get in at ground floor and make a huge impact on tremendous team! Salary based on experience

Job DescriptionAbout GoodPop GoodPop is a better-for-you frozen treat company on a mission to create delicious products using simple, organic ingredients. As a certified B Corp, GoodPop is committed not only to product quality, but to people and the planet. The team operates in a fast-paced, high-growth environment, partnering closely across operations, finance, and supply chain to bring products from raw materials to freezer shelves nationwide. Job Overview The Product Development Scientist will support product development and day-to-day R&D operations, working closely with the R&D Director to bring products from concept to commercialization. This role is highly hands-on and spans benchtop formulation, sample preparation, product testing, technical documentation, and scale-up support at co-manufacturing partners. Success in this role requires strong technical execution, attention to detail, and the ability to manage multiple work streams across development, documentation, and operations. ResponsibilitiesProduct Development • Develop new formulas, formula improvements, and product renovations at benchtop and pilot scale, • Produce samples for internal evaluation, retailer presentations, and product testing, • Design, run, and document shelf-life, stability, and product performance studies, • Evaluate new and alternative ingredients through comparison samples, sensory analysis, and written findingsTrials & Scale-Up, • Plan, support, and attend trial production at co-manufacturing facilities, • Provide on-site technical support during scale-up and commercializationDocumentation & Compliance, • Maintain bills of materials (BOMs), formulas, and batch documentation, • Develop nutrition facts panels and ingredient statements for new and revised products, • Write and maintain finished product specifications and internal ingredient specifications, • Manage supplier and co-manufacturer documentation (specs, COAs, certifications, batch sheets), • Support certification programs (Organic, Non-GMO Project Verified, Kosher)Lab Operations, • Help maintain R&D lab operations including inventory, sanitation, and equipment careCross-Functional Support Partner with Operations, Quality & Compliance, Procurement, and Marketing on R&D initiatives Requirements • Bachelor's degree in Food Science, Food Chemistry, Chemistry, Biology, or Nutrition, • 2-4 years of experience in the food industry, • Hands-on experience with benchtop and pilot-scale product development, • Strong attention to detail and organization, • Analytical mindset - comfortable with formula math, unit conversions, % solids, Brix, • Proficiency with Microsoft Excel, • Clear written and verbal communication skills, • Ability to work on-site in a lab environment and remain on feet for extended periodsPreferred, • Experience in frozen desserts, ice cream, or frozen novelty manufacturing, • Experience with nutrition analysis software (Tech Wizard, Genesis R&D, or equivalent), • Familiarity with ERP systems, particularly Microsoft Dynamics Business Central, • Experience supporting trials at contract manufacturers or co-packing operations, • Familiarity with FDA food labeling requirements (21 CFR) Department: Research & Development Reports to: R&D Director Location: Long Island City, NY (On-site 4 days/week) Type: Full-Time Travel: 10-20% (Co-manufacturing trials and production support)

Job Description Role Summary We are looking for a talented and highly motivated contract Lab Operations Associate Scientist/Scientist I to join the Lexeo Team in NYC to support the operations within our gene therapy laboratory. You will be expected to support the daily operations of the laboratory, ensuring that workflows run smoothly, safely, and efficiently. This role reports to the Lab Manager to oversee equipment, procure supplies, manage shipments, and ensure compliance with safety standards. The ideal candidate is organized, detail-oriented, and comfortable balancing administrative responsibilities with hands‑on lab support. The nature of the role will require in-person work. Primary Responsibilities • Assist in managing day‑to‑day lab operations, including inventory management, consumables ordering, managing a stock room, and equipment maintenance, • Maintain digital inventory of supplies, reagents, and equipment. Place orders and track deliveries, • Oversee equipment maintenance, calibration, and service records to ensure operational readiness, • Support onboarding and continuous training of laboratory staff on lab procedures and safety protocols, • Monitor the environmental elements of the laboratory with safety regulations, institutional policies, and quality standards, • Help develop and update standard operating procedures (SOPs) and documentation, • Coordinate shipping samples, supplies, and reagents to/from a biorepository, CDMOs, and the Lexeo lab, • Coordinate waste disposal, chemical storage, and safety inspections, • Serve as a point of contact for vendors, facilities, and service technicians, • Actively collaborate and communicate cross-functionally within Lexeo. The successful candidate will embrace this challenging role with enthusiasm, demonstrate the ability to work within a team, and maintain professionalism while getting things done quickly and efficiently. Attention to detail is expected. The ability to juggle many task at the same time meticulous and detail-oriented approach is crucial for maintaining accuracy.Required Skills and Qualifications, • Bachelor’s or Master's degree in a scientific discipline (e.g Biology, Chemistry, Biotechnology), • 5 years of experience in managing a lab (in industry or in combination with academia) with a deep understanding of lab safety, • Hands-on experience in a pharmaceutical/biotech environment; knowledge of gene therapy basis a plus, • Strong organizational skills with attention to detail and accuracy, • Ability to manage multiple priorities and meet deadlines in a fast-paced environment, • Excellent communication and coordination skills, • Familiarity with Benchling or Quartzy is beneficial Lexeo Therapeutics is a clinical-stage genetic medicine company headquartered in New York City, pioneering cardiac genetic medicine candidates to treat the root causes of inherited cardiovascular diseases. Our lead program, LX2006, targets cardiomyopathy associated with Friedreich’s Ataxia and anchors a broader pipeline addressing genetically defined conditions such as hypertrophic and arrhythmogenic cardiomyopathies. Backed by a strong financial foundation, Lexeo is positioned to translate groundbreaking science into durable clinical impact. Lexeo Therapeutics is an EEO employer committed to an exciting, diverse, and enriching work environment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionRadical AI, Inc. is an artificial intelligence company that is accelerating scientific research & development. We are at the forefront of innovation in the field of materials R&D, a critical driver for advancing our most cutting-edge industries and shaping the future. Breaking away from the traditionally slow and costly R&D process, Radical AI leverages artificial intelligence and machine learning to pioneer generative materials science. This innovative field blends AI, engineering, and materials science, revolutionizing how materials are created and discovered. Radical AI's approach speeds up R&D and addresses global challenges, setting new benchmarks in technology and sustainability. The opportunityWe are seeking a talented and forward-thinking alloys Materials Scientist with expertise in materials research and development to join our innovative team at the forefront of interdisciplinary research. In this role, you will leverage cutting edge experimental techniques to accelerate materials discovery, design, and optimization, contributing to groundbreaking advancements in materials science.Mission • Design and execute experiments to synthesize and characterize materials, leveraging AI algorithms to guide experimental design and interpretation., • Analyze and interpret large datasets generated from experiments, simulations, and external sources to extract valuable insights into materials properties and behavior., • Work closely with AI scientists and engineers to translate materials properties, identify structure-property relationships, and optimize materials performance for specific applications., • Stay current with advancements in materials science theory and experimentation and apply new methodologies and techniques to advance research objectives., • Communicate research findings effectively through technical reports, presentations, and scientific publications, contributing to the dissemination of knowledge and the development of intellectual property.About you, • PhD or Masters degree in Materials Science, Chemistry, Chemical Engineering, Polymers, or a related field, • Strong background in materials science principles, including materials synthesis and characterization., • Deep knowledge of materials characterization and testing, as well as familiarity with laboratory safety protocols., • In-depth industry knowledge of metal synthesis, including potentials, limitations, and key process and equipment suppliers., • Specialized metallurgical knowledge and experience in metallographic and fractographic interpretation, corrosion, oxidation and materials characterization techniques is desired., • Excellent analytical and problem-solving skills, with the ability to analyze complex datasets, identify patterns, and draw meaningful conclusions., • Strong written and verbal communication skills, with the ability to convey technical concepts and research findings to diverse audiences.Pluses, • Experience with AI-driven materials research, including machine learning models for materials property prediction, materials informatics, and data-driven materials discovery., • Familiarity with one or more software languages (Python, C++, MATLAB, etc.), • Prior experience in transitioning AI + computational research into production environments.What we offer, • A competitive compensation package also includes the best in benefits:, • Medical, dental, and vision insurance for you and your family covered at 100%, • Mental health and wellness support, • Unlimited PTO and 14+ company holidays per year, • 401K, • Work closely with a team on the cutting edge of AI research. Disclosure Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.

Job DescriptionSamba is an AI-powered media intelligence company on a mission to give marketers the complete picture of their audiences. Our AI indexes media consumption across millions of smart TVs and 2.5 billion web pages, combining that data with third-party signals through the Samba Knowledge Graph, a map of the real interests, behaviors, and purchase intent of 1.5 billion user profiles globally. Brands, agencies, publishers, and platforms use Samba to make smarter decisions across every stage of the marketing funnel. Samba TV is seeking a Product Manager to own our outcomes product suite. You'll be responsible for how we connect TV and digital media exposure to real-world business results—from website conversions to tune-in, brand lift, movie box office sales, and working with partners in the space. This role sits at the core of Samba's value proposition: proving that advertising works, and helping our clients understand exactly how and why.Outcomes measurement is the ultimate currency of modern advertising. Brands don't just want to know who saw their ad—they need to know what happened next. As the industry moves towards true business outcomes, Samba is uniquely positioned to bridge the gap between TV viewership and web intelligence and measurable real-world impact. You'll ensure our outcomes products are the most credible, scalable, and actionable in the market.What You'll Do: • Own the end-to-end product roadmap for Samba's outcomes and attribution capabilities, including conversion measurement, lift studies, and third-party data integrations, • Define requirements for attribution workflows—from third-party exposure or outcome data ingestion and audience matching to control group construction, results computation, and client-facing reporting, • Partner cross-functionally with data science, engineering, sales, and client success to build measurement methodologies that are both statistically rigorous and commercially compelling, • Develop and expand integrations with outcome signal providers across retail, automotive, travel, finance, and other key verticals—including point-of-sale data, website pixels, CRM feeds, and foot traffic signals, • Translate complex measurement concepts—incrementality, matched market testing, geo-based holdouts, media mix modeling—into clear product specs and client-ready narratives, • Build repeatable, scalable study frameworks that enable clients to move from custom one-off measurement engagements to always-on outcomes intelligence, • Stay ahead of industry shifts in measurement methodology, including the move toward incrementality as the new standard and the growing role of clean rooms in outcome attribution, • Define and track product success metrics including study turnaround time, methodology accuracy, client adoption, and renewal rates tied to measurement valueWho You Are:, • 3+ years of product management experience in ad tech, measurement, analytics, or data platforms, • Deep understanding of advertising attribution methodologies—conversion lift, brand lift, geo holdouts, incrementality testing, and multi-touch attribution, • Familiarity with the outcome signal landscape: retail data providers, foot traffic vendors, pixel-based conversion tracking, and 3P data onboarding, • Experience shipping measurement or analytics products that required close collaboration between data science, engineering, and client-facing teams, • Ability to navigate the tension between methodological rigor and commercial practicality—knowing when perfect is the enemy of shipped, • Strong communicator who can make statistics feel intuitive to a media buyer and make business requirements feel precise to a data scientist, • Track record of executing in ambiguous, fast-moving environments where measurement standards and client expectations are constantly evolving, • Hustler mentality: you build conviction with data, move with urgency, and close the loop between what we ship and what clients actually valueSamba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact. Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU , Samba Inc. is the data controller.

Job Description Garner's mission is to transform the healthcare economy, delivering high-quality and affordable care for all. We are fundamentally reimagining how healthcare works in the U.S. by partnering with employers to redesign healthcare benefits using clear incentives and powerful, data-driven insights. Our approach guides employees to higher-quality, lower-cost care, creating a system that works better for everyone. Patients achieve better health outcomes, employers spend healthcare dollars more effectively, and physicians are rewarded for delivering exceptional care rather than performing more procedures. Garner is one of the fastest-growing healthcare technology companies in the country. Our products are trusted by the most sophisticated employers and providers in the industry, and we are building a team of talented, mission-driven individuals who are motivated to make a meaningful impact on healthcare at scale. About the role: We are seeking an exceptional Data Scientist II to join our Central Data team. This role will report to the Director, Data Science & Analytics. This role is critical to shaping Garner's Product & Growth strategy - from evaluating the impact of our products to building models that drive engagement. You will collaborate with data, product & engineering to improve the effectiveness of Garner's member facing product – e.g., answering questions like, "what features of our product drive engagement?", "What is the best time of day and channel to outreach to members?", or "What data concepts do we need to build out to improve our understanding of what drives someone to engage with Garner?" Your work will directly impact our member-facing products and inform strategic product decisions. Where you will work: This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: • Identify and measure success of product efforts through goal setting, AB testing, forecasting, and monitoring of key product metrics to understand trends, • Own projects end to end including problem definition, implementation, validation, & iteration, • Research, develop, and maintain data pipelines, statistical models, and advanced analytical solutions, including AI & machine learning models, • Collaborate cross-functionally with data scientists, product leaders, engineering & operations teams to shape how we define product & member engagement metrics, apply statistical rules, and model member behavior, • Synthesize & present your work to Garner leadership to drive company level decisions, • Contribute to improving data science practices, tooling, and documentationWhat you will bring to the team:, • 2+ years of experience in data science, applied analytics, or a related quantitative field (industry, academia, or both), • 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data, • 2+ years of experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing, • Excellent verbal and written communication skills, with ability to present information and analysis results effectively, • A demonstrated ability to independently solve difficult problems and deliver high quality results to senior stakeholders, • A willingness to "roll up your sleeves" and do whatever is necessary to ensure company success, ideally in a startup environment Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time. Compensation Transparency: The target salary range for this position is $158,000 - $175,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k), Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at .

Job Description We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights. In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research. Your goal will be to help our company analyze trends to make better decisions. Responsibilities • Identify valuable data sources and automate collection processes, • Undertake to preprocess of structured and unstructured data, • Analyze large amounts of information to discover trends and patterns, • Build predictive models and machine-learning algorithms, • Combine models through ensemble modelling, • Present information using data visualization techniques, • Propose solutions and strategies to business challenges, • Collaborate with engineering and product development teams Requirements • Proven experience as a Data Scientist or Data Analyst, • Experience in data mining, • Understanding of machine-learning and operations research, • Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset, • Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop), • Analytical mind and business acumen, • Strong math skills (e.g. statistics, algebra), • Problem-solving aptitude, • Excellent communication and presentation skills, • BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred

Job Description A client of AlphaStaffHCM™ is searching for a Research Scientist who will work on the modeling, simulation, and architectural development of quantum and artificial intelligence (AI) computational structures intended for chip-scale implementation. The right candidate must be able to work onsite in Hoboken, NJ. Key Responsibilities: • Develop and simulate quantum and AI-based photonic architectures for on-chip, • implementation., • Translate high-level computational concepts into device-level and system-level, • simulation models., • Perform rigorous electromagnetic and Multiphysics simulations to evaluate optical,, • nonlinear, and quantum effects., • Model and simulate quantum photonic circuits and quantum gates under realistic device, • conditions., • Analyze fabrication tolerances and material constraints to assess design robustness., • Optimize photonic device structures for performance, scalability, and manufacturability., • Collaborate closely with fabrication and packaging teams to ensure simulation models, • align with process capabilities., • Support post-fabrication validation by correlating experimental results with simulation, • predictions., • Document modeling methodologies, simulation results, and architectural trade-offs for internal and external reporting Must Have Qualifications: • Ph.D. in Physics, Applied Physics, Electrical Engineering, or a closely related discipline., • Strong foundation in Photonics, Quantum optics, Nonlinear optics, • Demonstrated experience in simulation of photonic integrated circuits., • Experience modeling and simulating quantum gates/ quantum optical systems., • Understanding of semiconductor/TFLN and photonic chip fabrication processes, • Familiarity with chip testing and packaging considerations from a modeling perspective., • Software experience with Lumerica, Python, and Tidy3D Nice to Have Qualifications • Software experience with COMSOL Multiphysics, MATLAB, and/or Z-Max, • Demonstrated experience as a self-starter, • Demonstrated experience as a quick leaner Compensation and Perks • Salary range: $120,000-$150,000 annually, based on experience., • Medical, dental, and vision coverage., • Generous PTO and a retirement match., • 9:00-5:00 in office schedule Disclaimers: AlphaStaff, Inc. and the Client are equal employment opportunity employers and do not discriminate against any applicant or employee based on race, color, sex, sexual orientation, gender identity, religion, national origin, age, past or present military service, disability, genetic information, or any other basis protected by applicable federal, state, or local laws.

Job Description Dwight School is the first school in the Americas to offer all four International Baccalaureate programs from preschool to grade 12. Guided by our philosophy of igniting the spark of genius in every child, Dwight is an inclusive school that aims to meet the unique needs, abilities, and interests of each student. At the same time, Dwight challenges every student to develop intellectual independence, respect for diversity and belonging, and to become innovators and thought leaders. Known for its low student-teacher ratio, Dwight enrolls 1,100 students with 400 faculty and staff. Our School rests on three pillars: personalized learning, community, and global vision. As part of a leading global network of schools, Dwight offers employees exciting cross-campus opportunities. Additionally, with the support of The Dwight School Foundation’s generous grants, Dwight provides faculty professional development, enabling teachers to deepen their content knowledge and pursue their own sparks of genius to be shared with the community. At Dwight, we strive to ensure that our environment is welcoming — a place in which everyone can thrive — and an organization we are proud of. We recognize that this takes trusting relationships and ensuring that all individuals feel valued regardless of their backgrounds. At Dwight, we encourage diversity in all respects, including diversity of thought, and embrace innovation and foster collaboration and growth. We consistently strive to advance the equity, diversity and belonging of our community in all domains, including the curriculum, admissions, environment, and hiring. Our goal is to achieve and maintain equal employment opportunities, with policies in place to maintain a work environment free from discrimination. Science Teacher (Physics) Grades 9-12 Full Time, 7:30 am-4 pm Compensation commensurate upon experience: $75,000-$110,000 Position Overview Dwight School, an innovative preschool-grade 12 coeducational school on the Upper West Side of Manhattan, is currently offering in-person and remote academic programming for the 2026 - 2027 school year. We are seeking a self-directed, experienced, and energetic Science Teacher with an emphasis on Physics to begin in August 2026. Responsibilities • Foster a community where students are encouraged to learn, think, and act as a scientist., • Designing, developing and delivering lessons that are student centered, engaging, hands on and inquiry based., • Communicating effectively with students, parents and other teachers., • Grading efficiently and delivering regular feedback to students and parents, • Establishing classroom, lab, and field trip rules and regulations and ensuring that all students understand what is expected of them., • Creating an environment where students feel comfortable asking questions., • Display a commitment to diversity and creating a culture of equity, inclusion, and belonging in approach to teaching and learning, as they are recognized and valued by Dwight, • Complete an online anti-bias training program in the first year of teaching, • Bachelor’s Degree in Science, Science Education, or a science-related area required, • Master’s Degree in Science, Science Education or a science-related area recommended, • At least three year’s prior teaching experience in a High School setting, • A record of success teaching to a range of learners, • Experience with inquiry based learning in a Science class, • Experience with the International Baccalaureate Diploma Programme highly preferred, • Experience teaching to a range of learners, • Eagerness to contribute positively to the Dwight community, • Willingness to engage with and learn from people with diverse backgrounds and experiences Dwight School’s goal is to achieve and maintain equal employment opportunities. It is also the policy of Dwight School to maintain a work environment free from discrimination based on race, color, religious creed, national origin, gender, sexual orientation, age, disability, genetic information, veteran/military status, marital status, or other status protected by federal or state law, with regards to any term or condition of employment. Powered by JazzHR 6L6YjSk5LU

Job DescriptionRadical AI, Inc. is an artificial intelligence company that is accelerating scientific research & development. We are at the forefront of innovation in the field of materials R&D, a critical driver for advancing our most cutting-edge industries and shaping the future. Breaking away from the traditionally slow and costly R&D process, Radical AI leverages artificial intelligence and machine learning to pioneer generative materials science. This innovative field blends AI, engineering, and materials science, revolutionizing how materials are created and discovered. Radical AI's approach speeds up R&D and addresses global challenges, setting new benchmarks in technology and sustainability. The opportunityAs an AI Researcher specializing in generative models for materials discovery at Radical AI, you will help the development of the first commercial foundation model for materials science. Your role involves pioneering the application of generative models in the field of materials science, in particular by leveraging flow matching, diffusion, and LLMs. You will develop novel models and training techniques tailored for atomistic data in materials science. Your responsibilities include designing and conducting large-scale experiments to validate the most promising approaches in generative modeling. Collaborating closely with our engineering and computational materials science teams, you will play a crucial role in transitioning state-of-the-art models from research to production. Your expertise will contribute to the broader research community through publications in top-tier AI/ML venues like NeurIPS, ICML, and ICLR, alongside active participation in conferences and workshops. This role offers the unique opportunity to mentor and guide junior members of our technical team and research interns, fostering a culture of growth and innovation. Positions are available at various levels of seniority: Senior, Staff, and Principal.Mission • Lead and develop our generative foundation models in materials discovery., • Work in collaboration with various teams, in particular the quantum chemistry team, the atomistic simulation team, the engineering team, and the experimental team., • Conduct large-scale experiments to validate and refine promising approaches, collaborating closely with engineers to implement these models in production., • Develop rigorous benchmarks to validate and test the performance of our models., • Contribute to the AI and materials science research community through publications and active engagement in top-tier AI/ML venues like NeurIPS, ICML, ICLR, and our company blog, alongside active participation in conferences and workshops., • Tackle challenging problems with new and different ideas, creativity and contrarian thinking., • Mentor and guide junior team members and interns, promoting an environment of continuous learning and innovation.About you, • Ph.D., M.S., or B.S. in Computer Science, AI, Machine Learning, Applied Maths, or a closely related field, with a strong focus on deep learning and generative models., • At least 3 years of research experience in AI, with a proven track record in generative modeling, particularly in fields adjacent to materials science., • Working knowledge of various generative AI architectures, including transformers, diffusion models, CNFs, and flow matching., • Demonstrated experience in designing and running large-scale experiments in AI and machine learning., • Passionate about leveraging ML for science related problems and a commitment to doing world-class research., • Proficiency in Python and relevant ML libraries (e.g., PyTorch)., • Strong publication record in top-tier AI/ML conferences or journals., • Excellent collaboration and communication skills, capable of articulating complex technical ideas clearly and effectively.Pluses, • Prior experience in transitioning AI research into production environments., • Active involvement in the AI research community, with contributions beyond publications, such as organizing workshops or giving talks at conferences.What we offer, • A competitive compensation package also includes the best in benefits:, • Medical, dental, and vision insurance for you and your family, • Mental health and wellness support, • Unlimited PTO and 14+ company holidays per year, • 401K, • Work closely with a team on the cutting edge of AI research. Disclosure Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.

Job Description • Data Scientist, • Hybrid, NY, • Collaborate with the client in the sport sector to understand their business objectives and challenges and ensure the delivery of high-quality analytics/data science solutions., • Design and build end to end machine learning solutions and statistical frameworks across fan behavior., • Own the full modeling lifecycle: problem framing, feature engineering, model selection, cross validation and hyperparameter tuning, • Lead recurring analytical programs with a focus on reproducibility and automation., • Partner with data engineering to integrate model outputs into operational systems and stakeholder facing products., • Utilize your strong analytical and problem-solving skills to extract meaningful insights from data and contribute to data-driven decision-making., • Use variety of analytical tools (SQL, Python) and techniques (regression, decision trees, machine learning concepts etc.) to carry out analyses, create ML models and drive conclusions., • Support the integration of data science capabilities for the client to help solve tangible problems with measurable impact., • Bachelor's degree in economics, mathematics, computer science/engineering, operations research or related analytics areas, • 2+ years of hands-on experience in a data science role with a track record of shipping models into production., • Extremely proficient in SQL for robust data extraction and analysis., • Strong programming skills in Python., • Familiarity with Git and code/data version control., • Solid statistical foundation, • Exposure to NLP techniques for processing unstructured survey data., • Excellent communication, problem-solving, and critical thinking skills., • Self-started and willingness to take on challenging initiatives, • Effective time management and attention to detail, • Master's degree in a relevant field (e.g., Data Science, Analytics, Business Analytics).

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Expert Professionals — STEM Research Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities • Guide research teams to close knowledge gaps in STEM domains by surfacing edge cases, ambiguities, and frontier problems where current models underperform., • Design challenging, rigorous domain tasks and write accurate, well-reasoned solutions that demonstrate expert-level scientific and technical reasoning., • Evaluate tasks and solutions produced by AI agents and other contributors, providing clear written technical feedback grounded in domain expertise., • Develop evaluation frameworks and rubrics for assessing scientific reasoning quality across STEM domains. Must-Have • PhD (completed, enrolled, or equivalent research track) in Physics, Chemistry, Biology, Mathematics, Statistics, Computer Science, Electrical Engineering, Mechanical Engineering, Civil Engineering, Materials Science, or another STEM discipline., • 3+ years of research, academic, or industry experience in their primary STEM domain., • Demonstrated technical expertise in at least one domain: computational modeling, laboratory methods, data analysis, statistical inference, programming, or equivalent scientific methods., • Ability to commit to 40 hours per week during weekdays for the duration of the engagement., • Prior experience with data annotation, labeling, evaluation, or human feedback collection., • Upload resume, • AI interview based on your resume

Job Description Be Part Of A High-Performing Team: Join a sophisticated financial services technology environment supporting cybersecurity, data operations, and enterprise risk management initiatives. This team is focused on strengthening how insider risk is detected, measured, and governed across a large, regulated organization. The role sits at the intersection of cybersecurity, data science, analytics, and risk decisioning, contributing to a high-visibility program designed to centralize insider risk data and transform complex behavioral and enterprise signals into actionable insights. What's In Store For You: Engagement: W2 only (no C2C/1099) This is a hybrid opportunity based in Jersey City, NJ, supporting a cybersecurity data lakehouse initiative tied to insider risk and advanced analytics. The role offers the opportunity to work across Cybersecurity, HR, Legal, Compliance, Anti-Fraud, and enterprise protection teams while helping shape risk scoring, model governance, and executive-level reporting for a highly regulated environment. How You Will Make An Impact • Design, build, and refine quantitative models that help identify, assess, and prioritize insider risk across employees, contractors, vendors, and non-human identities., • Partner with data engineers, analysts, cybersecurity stakeholders, and business teams to centralize insider risk data within a cybersecurity data lakehouse., • Develop statistical, machine learning, and analytical frameworks for anomaly detection, classification, clustering, scoring, and behavioral risk modeling., • Translate large, complex enterprise datasets into clear risk signals, defensible models, and actionable business recommendations., • Support the creation of human-centric risk scoring methodologies that improve detection, investigations, governance, and regulatory readiness., • 5+ years of experience in data science, quantitative analysis, statistical modeling, or risk analytics., • Bachelor’s or Master’s degree in Data Science, Statistics, Applied Mathematics, Economics, Quantitative Finance, Computer Science, or a related discipline., • Strong experience developing statistical or machine learning models, including regression, classification, anomaly detection, and clustering., • Proficiency with Python and/or R, plus strong SQL skills for large-scale data analysis., • Experience working with complex enterprise datasets and translating analytics into operational or business decisions., • Background supporting Insider Risk, Fraud, AML, Cybersecurity, UEBA, Threat Analytics, or related risk programs., • Familiarity with identity/access data, endpoint telemetry, DLP, email, collaboration monitoring, or similar enterprise security datasets., • Understanding of model explainability, governance, validation, and documentation expectations in regulated environments., • Knowledge of employee lifecycle risk, behavioral analytics, or human-centric risk modeling is strongly preferred., • Strong communication skills with the ability to simplify complex analytical concepts for non-technical stakeholders.

Job Description StubHub is on a mission to redefine the live event experience on a global scale. Whether someone is looking to attend their first event or their hundredth, we're here to delight them all the way from the moment they start looking for a ticket until they step through the gate. The same goes for our sellers. From fans selling a single ticket to the promoters of a worldwide stadium tour, we want StubHub to be the safest, most convenient way to offer a ticket to the millions of fans who browse our platform around the world. The Role We're seeking a Senior Data Scientist to lead the science behind a best-in-class ticketing experience for fans, with a focus on the operational journey from ticket purchase through event entry. In this role, you will own and develop predictive and decisioning models that proactively identify and mitigate fulfillment issues, strengthen inventory validation, and optimize customer service policies — all while balancing fan experience with operational constraints. You will work on problems where getting it right matters: predicting issues before they impact fans, identifying emerging pain points at scale, and turning moments of potential failure into opportunities to build trust and loyalty. This includes building and productionizing models on both structured and unstructured data, such as LLM-backed pipelines that extract actionable signals from customer communications and support interactions. You will partner closely with product managers, analytics engineers, operations leaders, and other data scientists to translate ambiguous business problems into durable, production-ready data products, and to influence decisions that measurably improve the fan experience. Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA What You'll Do • Own the science behind ticket fulfillment: Drive reliability, ease of use, and customer satisfaction by crafting and deploying scalable, production-grade machine learning models that directly inform operational systems and decisions., • Drive data-informed strategy: Work with operations partners to shape roadmaps, using analysis and modeling to identify, prioritize, and size high-impact opportunities that can be implemented and sustained at scale., • Design for validation: Apply principles of experimentation and causal inference to ensure work products can be rigorously evaluated, defining offline validation and online testing strategies early in the design process., • Build the data foundation: Partner with platform and analytics teams to ensure data availability and quality, including event instrumentation, batch and streaming ETL, feature stores, and monitoring for model performance, bias, and drift., • 5+ years of industry experience in data science or machine learning, with an MS or PhD in mathematics, statistics, computer science, or a related quantitative field preferred., • Strong programming skills in Python, with experience using numerical and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, and gradient-boosting frameworks (e.g., LightGBM, XGBoost)., • Demonstrated experience building, deploying, and iterating on production machine learning models in cloud environments (e.g., AWS, Azure), including post-deployment monitoring and improvement., • Expertise working with large-scale data using modern analytics and compute platforms such as Snowflake, BigQuery, or Databricks, with strong proficiency in SQL., • Proven ability to establish data science methodology in new or ambiguous domains, owning work end to end—from stakeholder alignment and problem framing to delivery and measurable impact., • Experience applying machine learning to operational problem spaces such as ticket fulfillment, fraud detection, customer service, or trust and safety., • Experience with production ML platforms and workflows, such as Metaflow or comparable systems (e.g., Airflow-based ML pipelines, Kubeflow, SageMaker Pipelines, Prefect, Flyte), including model versioning, scheduling, and monitoring., • Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale., • Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact., • Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed.

Job DescriptionLead Data Scientist, Causal Inference & Clinical Outcomes Location: Remote Job Type: Contract or Full-Time (Flexible) The project is estimated to run for 16 weeks, beginning May 7, 2026, and concluding around August 27, 2026. Job Reports To: Director of Business Intelligence Salary Range: $100 - $155/hour About Jaan Health/Phamily Jaan Health is a leading AI-based care management company serving healthcare providers. For nearly a decade, the company has leveraged its easy-to-use, proprietary technology to enable health systems, medical groups, and ACOs to deliver high-quality, high-ROI proactive care to hundreds of thousands of previously underserved patients. Phamily, the company's core technology platform, has transformed chronic disease management with clinically tested AI and easy-to-use technology that enables physicians and care teams to offer high-touch, individualized patient care that has been proven to reduce investment in extra labor and the overall cost of care. Phamily helps ensure healthcare providers are compensated fairly for providing high-quality care between office visits, while improving the lives of patients with chronic diseases. Learn more at phamily.com. Job/Role Description We are seeking an analytical powerhouse to redefine proactive healthcare as our Lead Data Scientist for Causal Inference & Clinical Outcomes. In this 16-week engagement starting May 7, 2026, you will lead a rigorous clinical outcomes study for our key client, Silver Cross Medical Group (SCMG), to quantify the impact of our Advanced Primary Care Management (APCM) and Chronic Care Management (CCM) programs. Your primary mission is to provide empirical evidence answering two critical questions: Do patients in our programs have lower hospital readmission rates and higher discharge follow-up rates?. This role requires a specialist who can manipulate complex healthcare claims and EHR data to build an airtight, actuarial-grade causal inference framework. Additionally, you will audit and extract value from a previous analytics vendor's deliverables to close out their engagement. If you are a health-tech veteran who excels at translating complex statistical findings into compelling narratives for stakeholders, we want to hear from you. Key Responsibilities • Study Design & Execution: Lead a longitudinal, quasi-experimental study starting May 7 to measure clinical outcomes, specifically hospitalization frequency and discharge follow-ups., • Causal Inference Modeling: Apply advanced methodologies (e.g., propensity score matching) to observational data to estimate counterfactual patient outcomes with minimal bias., • Actuarial-Grade Validation: Develop and refine statistical models that will be thoroughly vetted and approved by customer actuaries., • Stakeholder Management: Serve as the primary analytical face to SCMG, gathering requirements and aligning on clinical/business definitions of success., • Data Storytelling: Translate complex statistical findings into compelling presentations and client-ready reports for both technical and non-technical leadership., • Vendor Audit & Wrap-up: Extract usable value from an existing outsourced study, close out the vendor contract, and integrate relevant findings into the final study., • Technical Infrastructure: Navigate and build analytics reporting infrastructure using SQL, Python, dbt, Redshift, and Looker., • Project Handoff: Ensure all code is clean and reproducible for final handover to the internal Phamily BI team.Requirements, • Health-Tech Expertise: Deep experience in causal inference, metric design, and clinical outcomes evaluation., • Data Proficiency: Extensive experience working with complex EHR and healthcare claims data., • Advanced Analytics Toolkit: Highly capable in Python, R, SQL, dbt, Redshift, and Looker., • Statistical Matching: Proven experience developing algorithms for high-dimensional statistical matching with large datasets., • Security Standards: Practical experience maintaining strict PHI security protocols while building data infrastructure., • Analytical Rigor: Ability to design and execute "actuarial-grade" studies that control for significant confounding variables., • Communication: Exceptional ability to synthesize technical data into narratives for non-technical clients., • Education: Advanced degree in a quantitative field (e.g., Data Science, Statistics, Health Economics, or Epidemiology).Preferred Requirements, • Entrepreneurial DNA: A 'builder' mentality with the ability to operate effectively in high-ambiguity environments where processes may not be fully fleshed out., • HEOR Consulting: Prior background as a Health Economics & Outcomes Research (HEOR) consultant., • Actuarial Alignment: Experience in presenting methodology to and gaining approval from health system actuaries.Work Style & Logistics, • This is a remote-first position., • The project is estimated to run for 16 weeks, beginning May 7, 2026, and concluding around August 27, 2026.Compensation & Benefits, • Competitive compensation commensurate with experience, • Potential to earn equity based on performance, • Medical, dental, and vision coverage for employees and dependents at a nominal cost, • Paid maternity leave, • FSA and Dependent Care account options, • 401(k) Eligibility after 6 months of full-time employment

Job Description Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. As a Generative AI Research Scientist, you'll work alongside our founders and team members to develop advanced generative models that can synthesize and design biological systems at multiple scales. Building upon our biological reasoning model, you'll focus on creating the generative capabilities that turn insights into innovations. * ⁠You will design and develop cutting-edge generative models specifically for biological data, creating AI systems that can generate novel molecular structures, protein designs, cellular components, and biological pathways. * You will design and implement state-of-the-art generative algorithms including diffusion models, language diffusion models, diffusion transformers, and flow matching approaches and tailor them to biological constraints and properties * You will train and scale innovative AI models using large, diverse biological multi-modal datasets across distributed GPU clusters. * You will solve challenging AI research problems at scale, tackling key aspects such as model architecture and scaling, pre-training and fine-tuning strategies, and rigorous evaluation methods. * Your work will span various advanced generative AI architectures, including transformers, diffusion models, and autoencoders, exploring and implementing these techniques to push the boundaries of biological AI. Who We're Looking For: * You have a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a relevant technical field. * You have a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. * You have a strong publication record in top-tier AI conferences or journals (e.g., NeurIPS, ICML, ICLR). * You have extensive hands-on experience building and training generative models, such as diffusion models, GANs, VAEs, normalizing flows, or autoregressive models. * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX). Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges. * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and taking pride in solving them. * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty. * You have excellent communication skills and can clearly articulate complex technical concepts. * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity. Bonus points: * You have experience applying machine learning to biological or chemical problems. * You have knowledge of physics, molecular biology, chemistry, computational biology, bioinformatics, cheminformatics or related fields. * You have experience with multi-modal learning. * You have contributed to open-source machine learning projects. * You have experience in developing efficient code in C/C++. Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $120K - $250K

Job DescriptionAbout Fusemachines Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.Salary Range: US$ 140,000-170,000/year Note: We are not considering OTP STEM visas neither H1B support for this roleRole Overview We’re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You’ll work across the ML lifecycle—from problem framing and data exploration to model development, evaluation, deployment, and monitoring—often in partnership with client stakeholders and internal delivery teams. You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems. Key Responsibilities • Problem Framing & Stakeholder Partnership, • Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)., • Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)., • Data Analysis & Feature Engineering, • Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses., • Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices., • Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions., • Model Development (Core ML), • Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)., • Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation., • Build time series models (statistical and ML/DL approaches) and validate with proper backtesting., • Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness., • Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making., • Deep Learning, • Build and train deep learning models using PyTorch or TensorFlow/Keras., • Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)., • Evaluation, Explainability, and Iteration, • Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports., • Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence., • Productionization & MLOps (Project-Dependent), • Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration., • Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans., • Documentation & Communication, • Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders., • Create documentation and lightweight demos that make results actionable.Success in This Role Looks Like, • You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)., • Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring., • Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly.Required Qualifications, • 3–8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)., • Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)., • Strong SQL skills (joins, window functions, aggregation, performance awareness)., • Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset., • Hands-on experience across multiple model types, including:, • Classification & regression, • Time series forecasting, • Clustering/segmentation, • Experience with deep learning in PyTorch or TensorFlow/Keras., • Strong problem-solving skills: ability to work with ambiguous goals and messy data., • Clear communication skills and ability to translate analysis into decisions.Preferred Qualifications, • Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)., • Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)., • Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)., • Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)., • Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)., • Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks), • Databricks certifications (Data Scientist, Data Engineer, or related)Nice-to-Have, • Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)., • Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products., • Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability.Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws. Important: Immigration Sponsorship Policy Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including: • Direct Company Sponsorship: Such as H-1B, J-1, or TN visas., • Employer of Record: Listing Fusemachines as the immigration employer on any government documentation. pYO5KHk85I

Job Description We are sharing a specialised part-time consulting opportunity for professionals experienced in data science, analytics engineering, business intelligence, SQL analysis, experimentation, data engineering, and structured data workflow review. This role supports current and upcoming remote consulting opportunities focused on structured data science review, analytics workflow analysis, business intelligence assessment, experimentation review, data pipeline evaluation, metric documentation, and high-quality project execution. Selected professionals will apply their data and analytics expertise to review realistic technical scenarios, evaluate analytical requirements, prepare structured written outputs, and support accurate, evidence-based data workflow tasks. Key Responsibilities Professionals in this role may contribute to: Analytics, BI & Metric Review • Review data scenarios involving SQL analysis, ad-hoc business questions, dashboard specifications, metric definitions, funnel analysis, cohort analysis, and reporting outputs, • Evaluate analytical outputs against source data, defined business logic, expected numerical results, and documented requirements, • Support structured review of SQL queries, BI dashboards, dashboard specs, metric documentation, and analytical summaries, • Review experimentation scenarios involving A/B test design, readouts, lift calculations, statistical significance, guardrail metrics, and decision criteria, • Evaluate experiment outputs against defined metrics, expected values, testing assumptions, and analytical standards, • Support structured review of data science workflows, Python-based analyses, statistical outputs, and business interpretation materials, • Review data engineering scenarios involving ETL/ELT pipelines, dbt models, data quality monitoring, warehouse schema design, Airflow or Dagster DAGs, and pipeline documentation, • Evaluate pipeline outputs, schemas, transformations, orchestration logic, and data quality checks against documented requirements, • Support structured review of data artifacts such as dbt models, schema diagrams, data contracts, test suites, DAGs, and warehouse documentation Strong candidates may have: • 3+ years of experience as a data scientist, analytics engineer, BI analyst, data analyst, product analyst, data engineer, decision scientist, or related data professional, • Working fluency in at least two areas such as advanced SQL, dbt, data warehousing, Snowflake, BigQuery, Redshift, experimentation, A/B testing, pipeline orchestration, metric modeling, or Python for analysis, • Familiarity with tools such as SQL, Python, dbt, Airflow, Dagster, Snowflake, BigQuery, Redshift, Databricks, Looker, Tableau, Mode, Hex, Metabase, Power BI, or similar data and analytics systems, • Comfort reading and preparing data artifacts such as SQL queries, dbt models, experiment readouts, dashboard specs, schema diagrams, metric definitions, and pipeline documentation, • Strong written communication skills and ability to explain data decisions clearly, • A degree or professional background in data science, statistics, mathematics, computer science, economics, engineering, business analytics, information systems, or a related quantitative field is helpful, • Experience in product, consumer, SaaS, marketplace, fintech, e-commerce, or data-mature company environments, • Familiarity with experimentation frameworks, metric governance, data quality monitoring, warehouse design, pipeline orchestration, or modern data stack workflows, • Experience preparing or reviewing SQL queries, dbt models, experiment readouts, dashboards, schema diagrams, funnel analyses, cohort reports, or data documentation, • Experience with Python-based analysis, statistical testing, data modeling, analytics engineering, or pipeline QA, • Apply data science and analytics expertise to structured remote project work, • Contribute to high-quality analytics review, experimentation assessment, BI documentation, and data pipeline workflow analysis, • Work on flexible, project-based assignments aligned with your technical background, • Use your data judgment in a focused, detail-oriented technical environment, • Independent contractor role, • Fully remote with flexible scheduling, • Part-time commitment depending on project availability, • Competitive rates between $75–$130 per hour depending on expertise, • Weekly payments via Stripe or Wise, • Projects may be extended, shortened, or adjusted depending on scope and performance This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: .

Job DescriptionAbout Fusemachines Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.Salary Range: US$ 140,000-190,000/yearRole Overview We’re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You’ll work across the ML lifecycle—from problem framing and data exploration to model development, evaluation, deployment, and monitoring—often in partnership with client stakeholders and internal delivery teams. You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems. Key Responsibilities • Problem Framing & Stakeholder Partnership, • Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)., • Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)., • Data Analysis & Feature Engineering, • Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses., • Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices., • Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions., • Model Development (Core ML), • Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)., • Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation., • Build time series models (statistical and ML/DL approaches) and validate with proper backtesting., • Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness., • Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making., • Deep Learning, • Build and train deep learning models using PyTorch or TensorFlow/Keras., • Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)., • Evaluation, Explainability, and Iteration, • Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports., • Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence., • Productionization & MLOps (Project-Dependent), • Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration., • Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans., • Documentation & Communication, • Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders., • Create documentation and lightweight demos that make results actionable.Success in This Role Looks Like, • You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)., • Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring., • Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly.Required Qualifications, • 3–8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)., • Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)., • Strong SQL skills (joins, window functions, aggregation, performance awareness)., • Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset., • Hands-on experience across multiple model types, including:, • Classification & regression, • Time series forecasting, • Clustering/segmentation, • Experience with deep learning in PyTorch or TensorFlow/Keras., • Strong problem-solving skills: ability to work with ambiguous goals and messy data., • Clear communication skills and ability to translate analysis into decisions.Preferred Qualifications, • Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)., • Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)., • Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)., • Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)., • Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)., • Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks), • Databricks certifications (Data Scientist, Data Engineer, or related)Nice-to-Have, • Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)., • Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products., • Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability.Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws. Important: Immigration Sponsorship Policy Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including: • Direct Company Sponsorship: Such as H-1B, J-1, or TN visas., • Employer of Record: Listing Fusemachines as the immigration employer on any government documentation. I0GDC3XJwj

Job Description Hi, we're Oscar. We're hiring a Data Scientist II to join our Data team. Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves - one that behaves like a doctor in the family. About the role: Oscar's data team is focused on pushing our understanding of this complex landscape of health care and insurance business. Insurance companies sit on a trove of data that is both broad and deep, spanning financial claims, clinical medical records, and rich product interaction data from our members. Connecting the dots across these datasets gives us unique insight into how the healthcare system functions and allows us to improve care coordination, better manage risk, build higher-performing provider networks, and create a standout consumer experience in our product. As a Data Scientist II you will drive data science projects across multiple teams and domains. In this role, you'll take ownership of analytical and modeling work, contribute to technical direction, and partner closely with business, engineering, product and data stakeholders to deliver impactful solutions. This is a mid-level role for data scientists who can operate independently, manage ambiguity, and apply advanced analytics or modeling techniques with minimal oversight. You will report into a leader on the Data team (Senior Data Scientist and above). This posting is representative of multiple roles, and final team placement will be determined during the interview process. Work Location: This position is a hybrid role based in our New York City office, Los Angeles Office, or Tempe Office requiring a hybrid work schedule with 3 days of in-office work per week Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid Pay Transparency: The base pay for this role is: $131,200 - $172,200 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses. Responsibilities: • Research, develop, and maintain data pipelines, statistical models, and advanced analytical solutions, • Own projects end-to-end, including problem definition, implementation, validation, and iteration, • Deliver high-quality analytical and modeling outputs with limited manager oversight, • Collaborate closely with data science peers and cross-functional partners across business units, • Help ensure data science processes and outputs align with broader team strategies and roadmaps, • Provide guidance or informal mentorship to junior data scientists or analysts when needed, • 3+ years of experience in data science, applied analytics, or a related quantitative field (industry, academia, or both), • 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data, • Master's degree in a quantitative or technical field, • Knowledge of or previous work experience in health care or health insurance, • Experience mentoring or supporting junior team members At Oscar, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change health care -- an experience made whole by our unique backgrounds and perspectives. Pay Transparency: Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. Full-time employees are eligible for benefits including: medical, dental, and vision benefits, 11 paid holidays, paid sick time, paid parental leave, 401(k) plan participation, life and disability insurance, and paid wellness time and reimbursements. Artificial Intelligence (AI): Our AI Guidelines outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts. Reasonable Accommodation: Oscar applicants are considered solely based on their qualifications, without regard to applicant's disability or need for accommodation. Any Oscar applicant who requires reasonable accommodations during the application process should contact the Oscar Benefits Team () to make the need for an accommodation known. California Residents: For information about our collection, use, and disclosure of applicants' personal information as well as applicants' rights over their personal information, please see our Privacy Policy.

Job DescriptionHinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role Join Hinge as a Senior Machine Learning Engineer, where you'll lead the application of AI and machine learning to effectively mitigate the impact of bad actors, remove policy violating content, and ensure user safety on the platform. Working closely with an expanding Trust & Safety team, you will collaborate with product managers, data scientists, engineers, and analysts to develop impactful AI/ML solutions. In this high-impact position within a small, dynamic team, you'll have the opportunity to play a foundational role in shaping how Hinge utilizes AI and machine learning in various contexts. Your expertise will be instrumental in creating a safer and more meaningful user experience on their journey to find an intimate connection.Responsibilities • Develop, deploy, and maintain end-to-end machine learning models to identify and mitigate bad actors, remove policy-violating content, and ensure user safety., • Design and implement scalable systems (e.g., using Spark, Kubernetes) to preprocess data, run inference, and manage post-processing pipelines., • Define standardized performance metrics, testing protocols, and evaluation processes to measure the effectiveness, identify and mitigate potential risks, and ensure fairness of AI solutions., • Ensure ongoing assessment and refinement of AI solutions, incorporating user feedback, business impact, and emerging ethical considerations., • Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to user safety., • Stay abreast of new trends and research in AI/ML that can be applied to Trust & Safety initiatives to improve detection, user safety, and stay ahead of potential threats.What We're Looking For, • Strong programming skills: Proficiency in languages like Python, Java or C++ and SQL, proficiency in at least one ML stack (e.g., PyTorch), and strong understanding of data pipelines, • Domain expertise: Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning real-time machine learning models for user facing products. Experience with applying expertise to fraud detection, content moderation, or related fields is a plus ., • System design & architecture: Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference., • Evaluation frameworks for LLMs: Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features., • Cloud and data platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with solutions like Databricks, Ray, or KubeFlow is a plus., • Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow., • Strategic technical leadership skills: Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives., • Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds., • Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation. Prior Experience, • 4+ years of experience, depending on education, as an MLE or data scientist. Previous experience working in Trust & Safety or related fields (e.g., fraud detection, content moderation, compliance) is preferred., • 2+ years of experience in applying end-to-end machine learning models, including data collection, model training, deployment, and monitoring in an industry setting, • 1+ years of experience integrating LLMs in real-world applications with the appropriate baseline metrics and evaluation methodologies., • 1+ years of experience utilizing ML infrastructure components such as a feature store, model training environment, model serving environment, observability, workflow orchestrator, etc. #Hinge .

Job DescriptionAbout Thea Energy: Thea Energy is leveraging recent breakthroughs in stellarator physics and engineering to create a faster and simpler approach to commercializing fusion energy. The company is reinventing the stellarator using computer-controlled arrays of planar coils thereby replacing the intricate, complex modular magnets required in all other stellarator architectures. Thea Energy is on a mission to create a limitless source of zero emission energy for a sustainable future. Position Overview:Thea Energy is looking for a highly motivated Burning Plasma Scientist to join our Physics team, focusing on modeling energetic particle confinement and transport. In this role, you will run high-fidelity simulations and pioneer the use of Machine Learning surrogates to accelerate our design cycles. You will work directly with our optimization team to ensure our magnetic topologies manage fast-ion loss and heat loads effectively.Key Responsibility Areas: • Execute and analyze high-fidelity simulations using particle-following codes to assess alpha particle and neutral beam ion confinement in 3D magnetic geometries, • Investigate Alfvén Eigenmode (AE) stability using kinetic-MHD hybrid codes and assess their impact on energetic particle transport, • Develop reduced-order models and ML surrogates trained on simulation databases to enable real-time prediction of pressure profiles, • Collaborate with the engineering team to iterate on coil designs and divertor configurations to minimize fast-ion losses, • Develop synthetic diagnostics (e.g. Fast-Ion Loss Detectors, Neutron Cameras) to bridge the gap between our models and future experimental campaignsIdeal Experience & Skillsets:, • PhD in Plasma Physics, Computational Physics, or related field (or Master’s / Bachelor’s with equivalent research experience), • Proficiency in programming languages commonly used in scientific computing (e.g. Python, Fortran, C++, or MATLAB), • Creative problem solving and proven ability to thrive in collaborative environments such as startups or research groups, • Willingness to collaborate with a diverse team of scientists and engineers within the company and externally, • Passion for advancing the field of fusion energy research, • Familiarity with kinetic, MHD or particle-following codes, • Experience developing Machine Learning surrogates for physical systems, • Familiarity with energetic particle diagnosticsCompany Benefits:, • Salary range $135,000-$210,000, • Comprehensive health benefits (e.g. medical/dental/vision), • Employee equity stock options

Job Description About impact.com impact.com is the world's leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L'Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results. Your Role at impact.com: We're seeking a Data Scientist to help build the next generation of recommendation systems powering our partnership automation platform. Our ecosystem connects a rich set of entities—advertisers, media publishers, creators, products, and consumers—and the relationships between them are where the real value lives. Your work will help surface the right partnerships, the right products, and the right content across this network at scale. You'll contribute to evolving our recommender stack toward a graph-based architecture leveraging semantic embeddings of entities and their relationships, applying cutting-edge techniques in representation learning, graph ML, and retrieval. The system needs to serve recommendations both in batch and real time, respond to dynamic user inputs, drive measurable value for end users across the platform, and remain reliable as the ecosystem grows. This role is hands-on and end-to-end. You'll own modeling and experimentation work for a defined area of the recommendation stack—from problem framing through productionization—in close partnership with Engineering, Product, MLOps, and Business Stakeholders. You're expected to bring (or actively develop) ML engineering chops so you can take a solution from prototype to production, and to be a relentless user of AI coding agents to multiply your output and accelerate iteration. What You'll Do: Core Responsibilities Multi-entity recommendations across the partnership graph Design, build, and evaluate recommendation models that operate across heterogeneous entities—advertisers, publishers, creators, products, and consumers—and the relationships between them. Frame problems in terms of the partnership graph and apply techniques appropriate to each surface, including candidate generation, ranking, reranking, and personalization. Graph-based modeling & semantic embeddings Contribute to evolving our architecture toward graph-based approaches: learn semantic embeddings of entities and relationships, apply graph neural networks or attention aware graph transformer models where they add value, and build representations that generalize across surfaces and use cases. Stay current with cutting-edge techniques in graph ML, representation learning, and modern recommender architectures, and bring relevant ideas into the platform. Batch and real-time serving Build models and pipelines that serve recommendations in both batch and real-time contexts. Partner with Engineering on retrieval infrastructure, vector search, feature stores, and low-latency serving patterns. Make pragmatic tradeoffs between model sophistication, latency, cost, and freshness based on the surface and use case. End-to-end ML delivery & ML engineering Own the full lifecycle of your work: data and feature design, model development, evaluation, launch, monitoring, and iteration. Build production-grade pipelines, write code that other engineers can extend, and partner with MLOps on reproducibility, observability, and reliability. Use AI coding agents aggressively to accelerate prototyping, refactoring, debugging, and shipping—we expect this to be a core part of how you work, not an occasional aid. Experimentation & measurement Design offline evaluation (offline replay, counterfactual evaluation, holdout sets) and online experiments (A/B tests, holdouts, interleaving) to quantify model impact. Apply appropriate statistical methods, recognize common pitfalls in recommender evaluation (position bias, feedback loops, selection effects), and translate results into clear recommendations for product and engineering partners. Cross-functional collaboration Work closely with Product, Engineering, and Business Stakeholders to translate platform goals into measurable model outcomes. Communicate findings, tradeoffs, and recommendations clearly to both technical and non-technical audiences. Document your work so that models, features, and decisions are understandable and reproducible by others. What You Bring: • 3+ years of experience in data science / applied ML, with a track record of shipping production models that delivered measurable user or business impact., • Strong Python and SQL skills; experience working with large-scale data and distributed compute (Spark/Databricks or equivalent)., • Hands-on experience building recommendation or ranking systems—candidate generation, learning-to-rank, retrieval and reranking, or implicit feedback modeling., • Experience with embeddings and representation learning for users, items, content, or other entities., • ML engineering capability (or strong willingness and demonstrated ability to develop it): you can build, ship, and maintain production pipelines—not just prototypes in notebooks., • Strong experimentation skills: designing and analyzing A/B tests, interpreting results, and communicating findings to stakeholders., • Relentless user of AI coding agents in your day-to-day workflow, with a clear sense of where they accelerate you and where they don't., • Insatiable curiosity about new techniques, architectures, and tools—and a track record of teaching yourself things quickly. You read papers, try new tools, and bring ideas back to the team., • Strong problem-solving instincts and the ability to operate with growing autonomy in ambiguous, evolving spaces.Preferred / Nice to have, • Experience with graph-based ML: graph neural networks (KGAT, transformers or similar), graph-aware retrieval, or knowledge graph embeddings., • Experience with modern deep learning recommender architectures (two-tower, sequence/transformer-based recommenders, multi-task ranking)., • Familiarity with vector search and vector databases (FAISS, ScaNN, Vespa, Milvus, or similar) and approximate nearest neighbor methods., • Experience with real-time ML serving, feature stores (Feast, Tecton, or equivalent), and low-latency inference patterns., • Exposure to contextual bandits, reinforcement learning, or off-policy evaluation in recommendation settings., • Familiarity with PyTorch/TensorFlow and PyTorch Geometric / DGL for graph workloads., • Familiarity with GCP (Vertex AI, BigQuery, Cloud Run) and/or mature MLOps practices (CI/CD for ML, monitoring, drift detection)., • Experience in adtech, martech, e-commerce, or two-sided/multi-sided marketplace recommendations.What Sets You Apart, • You think in terms of user and business outcomes, not just model metrics, and you connect modeling choices to real value delivered through the platform., • You're rigorous about measurement but pragmatic about shipping—able to deliver MVPs and iteratively evolve them into durable production systems., • You're a relentless learner. New papers, new tools, new architectures—you find them, try them, and figure out where they fit. You don't wait to be told what to learn., • You use AI coding agents like a power user: they're a force multiplier in your hands, not a crutch., • You have engineering instincts—you care about code quality, system design, and operability, not just model performance., • You're comfortable with messy data, noisy feedback, edge cases, and ambiguous problem spaces, and you excel at iterative improvement. *This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Benefits and Perks: At impact.com, we believe that when you're happy and fulfilled, you do your best work. That's why we've built a benefits package that supports your well-being, growth, and work-life balance. • Medical, Dental, and Vision insurance, • Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled, • Flexible spending accounts and 401(k), • Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life., • Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health., • A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval., • Investing in Your Growth: We're committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses., • Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver., • Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors. #LI_NewYork

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Environmental Science Expert Type: Contract Compensation: $50–$70/hour Location: Remote Role Responsibilities • Build a realistic digital workspace centered on the Drive folders you use daily. Include site assessment reports, permit applications, monitoring data summaries, and more. Represent platforms like Esri ArcGIS, SAS, MATLAB, and Socrata., • Design multi-step tasks grounded in your real workflows. Require navigating multiple apps, files, and stakeholders to challenge frontier AI agents., • Collaborate with other environmental-science experts to design the environment, shape task scope, and review scenarios for realism and rigor., • Work asynchronously with research teams to refine task designs and evaluation criteria for environmental-science agent benchmarks. Must-Have • 3+ years of full-time experience at a federal/state environmental agency, major environmental consulting firm, F500 sustainability team, or R1 university., • Background in environmental assessment and compliance, air, water, or waste permitting and monitoring, contaminated-site investigation/remediation, corporate sustainability, ESG reporting, or climate-risk analysis., • Day-to-day use of Esri ArcGIS, Google Maps Platform, SAS, MATLAB, and Socrata., • Upload resume, • AI interview based on your resume

Job DescriptionAbout Fusemachines Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government. Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI. About the Role A Lead Data Scientist is responsible for designing and implementing data-driven solutions to complex business problems. The role requires extensive experience in data analysis, agentic AI, statistical modeling, machine learning, and data visualization, as well as the ability to lead a team of data scientists and collaborate with cross-functional teams. Responsibilities • Team Leadership: Lead a team of data scientists to develop innovative solutions to complex business problems. Mentor and develop the skills of junior data scientists and provide feedback and guidance to help them improve their work., • Collaboration: Collaborate with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers to develop and implement data-driven solutions., • Strategic Assessment: Assess the business needs of clients and identify areas where AI can be used to improve processes, reduce costs, or increase revenue., • Solution Design: Design and implement statistical models, machine learning algorithms, predictive analytics models, and agentic systems to solve business problems., • Communication: Communicate technical insights and recommendations to non-technical stakeholders in a clear and concise manner., • Continuous Learning: Stay up-to-date with the latest developments in data science, machine learning, and artificial intelligence, and apply new technologies and techniques to solve business problems., • Pipeline Management: Responsible for developing, implementing, and managing end-to-end machine learning pipelines. This will involve building, deploying, and maintaining machine learning models, as well as ensuring data quality and system stability. Requirements for the Role, • Education: Bachelor's, Master's, PhD, or advanced training in applied mathematics, engineering, computer science, or a similar related field., • Experience: 6+ years of total experience in Data Science, Machine Learning & Generative AI., • Cloud Computing: 4+ years of hands-on experience with AWS, including deep expertise in deploying models and managing compute environments., • IBM WatsonX: 2+ years of hands-on experience with IBM WatsonX, • Agentic AI Tools: Experience with LangGraph, Google ADK or similar., • Agentic Architectures : Experience with advanced RAG & multi-agent systems., • Programming: Strong programming skills in languages such as Python, R, C++, and SQL., • Frameworks: Hands-on experience with ML frameworks, such as PyTorch or TensorFlow. XDOyWllq0r

Job Description Hi, we're Oscar. We're hiring a Senior Data Scientist to join our Data Team. Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family. About the role: We are a Data Science team at Oscar dedicated to improving the Member Experience by embedding advanced analytics into our core technology and operations. We focus on building data products that bridge the gap between complex health insurance workflows and seamless, member-centric service. You will drive the evolution of our member-facing tools by developing the LLM frameworks and ML models that underpin our automated support systems and digital interfaces. You will be responsible for evaluating both tool performance and member behavior to surface deep insights that inform our broader product and operations strategy. You will report into the Lead Data Scientist. Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid Pay Transparency: The base pay for this role is: $163,944 - $215,176.50 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants and annual performance bonuses. Responsibilities: • Works with team and manager to impact longer term strategies and roadmap, • Sets shorter term roadmap for team, • May manage data scientists and/or analysts, • Interacts and collaborates closely with data and business counterparts across functional areas, • Researches, develops, and maintains data pipelines, statistical/ML models, and/or advanced analyses, • Compliance with all applicable laws and regulations, • 4+ years of industry or other quantitative technical fields (which may include academia)., • 3+ years of work experience working with SQL, R, and/or Python to query, manipulate and analyze data, • Advanced degree in a quantitative or technical field, • Experience in the healthcare, finance and/or insurance industries At Oscar, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change health care -- an experience made whole by our unique backgrounds and perspectives. Pay Transparency: Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. Full-time employees are eligible for benefits including: medical, dental, and vision benefits, 11 paid holidays, paid sick time, paid parental leave, 401(k) plan participation, life and disability insurance, and paid wellness time and reimbursements. Artificial Intelligence (AI): Our AI Guidelines outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts. Reasonable Accommodation: Oscar applicants are considered solely based on their qualifications, without regard to applicant's disability or need for accommodation. Any Oscar applicant who requires reasonable accommodations during the application process should contact the Oscar Benefits Team () to make the need for an accommodation known. California Residents: For information about our collection, use, and disclosure of applicants' personal information as well as applicants' rights over their personal information, please see our Privacy Policy.

Job Description Garner's mission is to transform the healthcare economy, delivering high-quality and affordable care for all. We are fundamentally reimagining how healthcare works in the U.S. by partnering with employers to redesign healthcare benefits using clear incentives and powerful, data-driven insights. Our approach guides employees to higher-quality, lower-cost care, creating a system that works better for everyone. Patients achieve better health outcomes, employers spend healthcare dollars more effectively, and physicians are rewarded for delivering exceptional care rather than performing more procedures. Garner is one of the fastest-growing healthcare technology companies in the country. Our products are trusted by the most sophisticated employers and providers in the industry, and we are building a team of talented, mission-driven individuals who are motivated to make a meaningful impact on healthcare at scale. About the role: We are seeking an exceptional Data Scientist to join our Garner Health Intelligence team to help build and evolve our provider data insights. You'll work with our clinical researchers, data scientists, and data engineers to improve the rules and models we use to evaluate provider performance – e.g., answering questions like, how do we know which providers deliver better surgical outcomes or what data concepts do we need to build out to improve our analysis. Your work will directly impact our member recommendations and provider-facing data products. Where you will work: This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: • Partner with data scientists and clinical experts to shape how we define provider performance metrics, apply statistical rules, and model provider behavior, • Drive the evolution and construction of tools we use to write, assess, and combine rules measuring provider behaviors, • Build and maintain data-driven algorithms, including AI and machine learning models, to improve our provider recommendations estimates., • Design scalable data pipelines that ingest, clean, and enrich healthcare provider data., • Collaborate cross-functionally with product, engineering, research, and operations teams to translate business needs into data-driven solutions.The ideal candidate has:, • 2-5 years professional experience in data science, product analytics, and/or healthcare, • A demonstrated ability to independently solve difficult problems and deliver high quality results to senior stakeholders, • Strong Python and SQL skills, • A willingness to "roll up your sleeves" and do whatever is necessary to ensure company success, • Experience working in a rapidly evolving startup environment, • A desire to be a part of our mission to improve the U.S. healthcare system, • A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedbackTechnologies we use:

Job Description Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would — dramatically improving productivity for experienced teams, while making video creation accessible to anyone. We’re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you’ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. More about us Product (Captions by Mirage) Research (Seeing Voices, technical-white-paper) Updates (Mirage on X / twitter) TechCrunch, Forbes AI 50, Fast Company (press) Our Investors We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more. Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) About the Role We’re looking for a Data Scientist to help power our marketing strategy. In this role, you’ll partner with Marketing, Product, and Finance to improve acquisition performance, refine attribution, and build the measurement foundations that guide our company’s growth. As the first Data Scientist dedicated to marketing analytics, you will define core success metrics, evaluate funnel performance, and uncover insights that shape our go-to-market strategy. Key Responsibilities * Analyze acquisition, lifecycle, and overall marketing performance to surface trends, identify funnel gaps, and highlight opportunities to improve efficiency and customer value. * Build and maintain predictive models that support forecasting, customer understanding, targeting, and personalization. * Develop and improve marketing measurement frameworks to better understand channel impact, attribution, and drivers of growth. * Conduct deep analyses of customer behavior, segments, and retention patterns to inform marketing and product strategy. * Design, run, and evaluate experiments (e.g., A/B tests) to measure the impact of marketing initiatives and guide decision-making. * Assess multi-channel campaign performance and provide clear recommendations to marketing partners to improve outcomes. * Work closely with cross functional teams and leadership to enhance data quality, evolve marketing datasets, and support scalable analytical workflows. * Communicate insights clearly and effectively, turning complex analyses into actionable recommendations for leadership and cross-functional teams. Requirements * Minimum of 5 years of experience in data science, marketing data science, or growth analytics within B2C, B2B, e-commerce, or SaaS environments. * Advanced proficiency in SQL and Python, including experience with data manipulation libraries and statistical modeling. * Hands-on experience with modern cloud data warehouses (e.g., BigQuery) and building scalable data models or pipelines for analytics. * Strong understanding of marketing measurement, including CAC, CLV, ROAS, funnel analytics, incrementality testing, and attribution methods (MMM, MTA, SKAN). * Experience with predictive modeling, such as LTV, churn, conversion propensity, clustering, and time-series forecasting. * Familiarity with mobile measurement partners, including AppsFlyer or Adjust, and mobile attribution concepts. * Experience designing and evaluating experiments, with a solid grounding in statistical testing, causal inference, and uplift modeling. * Demonstrated ability to work cross-functionally, partnering with Marketing, Product, Finance, and Data Engineering stakeholders. * Exceptional analytical and problem-solving skills, with the ability to break down ambiguous problems and operate autonomously in fast-paced environments. * Clear and effective communication skills, with the ability to convey complex technical insights to non-technical audiences. Benefits: * Comprehensive medical, dental, and vision plans * 401K with employer match * Commuter Benefits * Catered lunch multiple days per week * Dinner stipend every night if you're working late and want a bite! * Grubhub subscription * Health & Wellness Perks * Multiple team offsites per year with team events every month * Generous PTO policy Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please note benefits apply to full time employees only. Compensation Range: $150K - $200K

Job Description About the Role: We are in search of an exceptional Machine Learning Engineer to join our accomplished team. In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary focus on Ad Score and Ad Account Health. You will play a crucial part in delivering actionable insights and solutions to our clients, and your work will be integral to our mission. Responsibilities include but are not limited to; • ML Model Development: Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health., • Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization., • Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training., • Model Evaluation: Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement., • Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs., • Collaboration: Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless integration of data science solutions into our products., • Master's or Ph.D. in a related field with a strong academic background., • Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models., • Expertise in machine learning techniques, including but not limited to regression, classification, clustering, and deep learning., • Proficiency in data manipulation, feature engineering, and model evaluation., • Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit-learn., • Excellent communication skills and the ability to collaborate effectively within cross-functional teams., • A passion for continuous learning and staying updated with the latest trends and technologies in data science., • Strong problem-solving abilities and the capacity to translate complex data into actionable insights.Required knowledge of:, • Python, • SQL, • Cloud Platforms (GCP, AWS, Azure), • Data Warehouses (BigQuery, Snowflake, Redshift), • LLMs / AI APIs, • Git / GitHubNice to have:, • Data Transformation (dbt), • Semantic Layers (Cube, Looker, dbt Metrics), • TypeScript, • Bayesian modeling experience - ideally Marketing Mix Models (PyMC, Stan, or similar..). Understands priors, MCMC sampling, posterior diagnostics., • Causal inference / experimentation- geo experiments (matched markets), A/B testing at scale. Familiar with incrementality measurement., • Marketing/advertising domain- understanding of attribution, media channels (paid social, search, display, video), campaign structures., • Unlimited vacation policy, • Monthly Phone Stipend, • Comprehensive Medical, Dental, and Vision insurance options, • 401(K) plan with matching, • Dog friendly office, • Hybrid work opportunity, • Professional Development Program, • Bonus Perk - Seamless allowance Total compensation based on education, experience, and skills level ($90,900-$254,100) * Level 1 - Possesses essential capabilities * $90,900-$123,540 * Level 2 - Possesses developing capabilities * $123,540-$156,180 * Level 3 - Possesses notable capabilities. * $156,180-$188,820 * Level 4 - Possesses strong capabilities. * $188,820-$221,460 * Level 5 - Possesses advanced capabilities. * $221,460-$254,100 About WITHIN WITHIN is the world's first Performance Branding company, partnering with some of the biggest brands in the world to drive business growth through innovative marketing strategies. Our integrated operating model collapses the traditional marketing silos between creative and media, performance and brand, and across media channels. With a full suite of offerings including media, creative, SEO, Lifecycle, Retail Media, Affiliate and Influencer, we're able to work with our brand partners in an integrated fashion, allowing us to align marketing strategies back to core business objectives. Client teams at WITHIN are trained on how to always act as a trusted business partner, acting as a fiduciary to client needs above our own. Teams at WITHIN have the ability to work with iconic brands such as The North Face, Timberland, Ben and Jerry's and Jose Cuervo. Everyone at WITHIN wants to grow and be challenged. It's a collaborative place made up of small, closely knit and versatile teams that are fast and adaptive to solve problems and build systems. Check out some of our work! We weave AI into everything we do, using the latest tech across all teams to innovate, work smarter, and make better decisions. Whether it's in creative, operations, or anything else, AI helps us level up and do things at a whole new scale. We expect our people to use AI in their daily work, fully embracing it as a critical tool to help us succeed. Join Our Network! Stay connected with us and be the first to know about new opportunities, industry insights, and updates. Follow us on: • LinkedIn, • WhatsApp Community, • Instagram, • New York City: 43-01 22nd St, Suite 602, Queens, NY 11101, United States, • Bogotá: WeWork Av. Carrera 19 #100-45 Usaquén, Piso (Floor) 10, Bogotá, Distrito Capital de Bogotá 110111, Colombia, • Mexico City: Av. Insurgentes Sur 1082, Piso (Floor) 2, Oficina 2008, Ciudad de México, CDMX 03100, México