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Title: Marketing Data Engineer Location: Remote US Duration: 12 months Compensation: $60-80/hr Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S. As a Data Engineer in the Marketing Analytics area you will have the opportunity to work across family of products. Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide. Responsibilities Work with the MarTech, Marketing Data Science and Data Ops teams, translating their needs into tangible analytical solutions to improve marketing efficacy by providing impactful insights through streamlined and automated reporting Design and Develop data models, pipelines, dashboards, and other analytic solutions to support Marketing programs and campaigns Solve data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources Collaborate with engineers, data scientists, program/product managers and marketers to understand data needs, representing key data insights in a meaningful way Conceptualize data architecture for large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems Implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues Produce clear, concise, accurate, and decision-ready analytical deliverables; independently validate all AI-assisted output for correctness, originality, and business relevance Minimum Qualifications Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent 5+ years of experience where the primary responsibility involves working with data. This could include roles such as data engineer, data scientist, data infra, or similar positions 5+ years of experience with SQL, ETL, data modeling, data visualization and at least one programming language (Python is preferred) Preferred Qualifications: Experience building and maintaining data integrations with advertising and marketing technology platforms (e.g., Meta, Google Ads/DV360/CM360, TikTok, Salesforce), including collecting ads performance data via APIs, webhooks, or batch file imports, and managing data pipelines & and business intelligence solutions that support marketing measurement, reporting, and decision-making. Experience building and maintaining survey data infrastructure: collecting data from survey platforms (Qualtrics, Medallia, custom web apps) via APIs, webhooks, or batch imports, and designing flexible data models that support storage, transformation, and modeling of complex questionnaire responses About INSPYR Solutions Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about . INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, or any other protected status. INSPYR Solutions complies with all applicable laws governing nondiscrimination in employment in every location in which the company has facilities. Applicants requiring reasonable accommodation during the application or interview process should contact for assistance. Information collected and processed through your application with INSPYR Solutions (including any job applications you choose to submit) is subject to INSPYR Solutions' Privacy Policy and INSPYR Solutions' AI and Automated Employment Decision Tool Policy: https://www.inspyrsolutions.com/policies/. By submitting an application, you are consenting to being contacted by INSPYR Solutions through phone, email, or text.

About Sapio Sciences Sapio Sciences is on a mission to accelerate scientific drug discovery and high-throughput clinical and diagnostics for our clients and partners. The Sapio team consists of expert and highly collaborative scientists, software developers, and professionals passionate about providing a best-in-class lab informatics platform and industry-specific solutions. Sapio is one of the few software providers to offer a truly unified and highly configurable lab informatics platform and a broad suite of purpose-built solutions. The Sapio platform makes it easy for scientists, laboratory, and bio/informatics professionals to streamline and manage their end-to-end laboratory operations, from instrument data integration to workflow and experiment setup to sample and materials management, data management, and scientific data analysis and reporting. Working at Sapio At Sapio, we’re not just building lab informatics solutions. We’re creating tools made for the scientist and motivated to make the world a better place. We understand that lab informatics is about more than managing data or connecting workflows. It’s about making life easier for the scientist and making scientific progress faster for everyone. Our platform delivers the levels of configurability, usability and insight that scientists have only ever dreamed of. We’re a team of scientists, developers and innovators who question convention and stay focused on what matters most - advancing drug discovery science. We challenge the status quo and respond to the needs at the heart of science with powerful solutions that are simple to use, effortless to evolve and downright easy to love. As part of the Sapio team, you’ll work in a collaborative and forward-thinking environment where your ideas are valued, your growth matters and your work makes a difference. We’re proud to partner with leading labs around the world, from ambitious start-ups to global organisations, who trust Sapio to support discovery, development and diagnostics with industry-first science-aware solutions. What you'll be doing • Interpret customer requests and translate them into functional requirements (recognize the distinction between user requests from the underlying true needs), • Documentation of business processes and workflow (‘as is’ and ‘to be’) using swim lane diagrams, • Identify customers key success criteria and ensure they are tracked and measured within the solution, • Maintain a thorough understanding of the Sapio Sciences product portfolio and how it is configured, • Effectively provide end user training on customized solution to show how the implementation met customer's goal, • Be able to perform configurations of the workflow/experiment in the Sapio Platform, and/or in some cases create wireframe mockups of the workflow/experiment, • Effectively document, communicate (oral and written) and explain technical material, • Perform root cause analysis, uncover critical business requirements, and facilitate solution delivery, • Expected to function independently and produce results that meet standards of quality, timeliness, and acceptability with minimal supervision, • Liaise with the product to ensure new customer driven feature requirements are captured, • Become our customer’s trusted technical partner, regularly review their deployment to ensure successful leverage our full product and service portfolio, • Work closely with the Sapio Sciences US team to establish scalable processes and working methods, • Meticulously manage all BA related deployment services documentation, • As needed, assist in testing sprint deliverables to ensure they meet requirements Requirements • Previous experience with LIMS or ELN software, • Life Sciences experience working within a Lab (preferably introducing new IT solutions), • A BS/BA degree or equivalent in Life Science (e.g. molecular biology, chemistry), • Qualified in lean Six Sigma, • Working knowledge and experience with JIRA and Confluence, • Substantial experience of effectively managing external stakeholders including strong communication skills and ability to build working relationships at all levels, • Experience leading external client workshops, documenting business needs and outcomes, • Proven organizational skills, with the ability to deliver agreed workload within deadlines while maintaining a high degree of accuracy and attention to detail, • Strong analytical, problem solving, interviewing, data analysis and fact-finding skills, • Excellent listening and presentation skills Our People At Sapio Sciences, our people are at the heart of everything we do. Our lab informatics solutions are powered not just by technology, but by a shared commitment to our core values—what we proudly call The Sapio Seven, aka EMBRACE: • Embrace the future • Make a difference • Be true partners • Remember why we’re here • Act with empathy • Commit to transparency • Excel in quality These values shape how we work, how we grow, and how we deliver impact for our clients every day. Reasonable Adjustments We are committed to ensuring an inclusive and accessible recruitment process. If you require any reasonable adjustments, at any stage across the application, interview & assessment processes then please let us know. We will work with you to support your needs in confidence. Diversity, Equity & Inclusion We do not discriminate based on race, colour, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, or any other status protected by law or regulation. We intend that all qualified applicants be given equal opportunity and that selection decisions are based on job-related factors. We are committed to creating a diverse and inclusive workplace and encourage applications from all qualified individuals. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.

Drug Discovery Scientist Position: Drug Discovery Scientist Type: Hourly Contract Compensation: $60–$90/hour Location: Remote About the Opportunity This opportunity is for experienced Drug Discovery Scientists to contribute to an advanced AI research and evaluation project focused on pharmaceutical research and development. You'll apply your scientific expertise to design realistic, evidence-driven drug discovery problems that require AI models to reason through incomplete, indirect, and potentially misleading scientific evidence. You'll create research prompts, build supporting data rooms using real source-grounded information, develop rigorous grading frameworks, and validate the resulting tasks. The role is ideal for experts who can distinguish genuine scientific reasoning from pattern matching and confidently evaluate the quality of complex research conclusions. Responsibilities • Design challenging, realistic drug discovery research problems based on authentic scientific workflows., • Develop research scenarios where the correct conclusion must be derived from multiple pieces of evidence rather than directly stated., • Build comprehensive data rooms using real, source-grounded scientific data and documentation., • Ensure every decisive scientific value and piece of evidence can be traced back to a reliable source., • Create detailed grading documents and evaluation rubrics that assess scientific reasoning and substantive conclusions., • Evaluate AI-generated research outputs for scientific accuracy, logical consistency, and defensibility., • Run verification and calibration processes to ensure tasks are reproducible, appropriately difficult, and objectively scorable., • Identify weaknesses in task design, evidence, or evaluation criteria and revise them accordingly., • Provide expert judgment on scientific questions, task difficulty, and the quality of AI reasoning., • Collaborate with project reviewers and other domain experts to refine research tasks. Required Qualifications • Professional expertise in one or more of the following areas:, • Mechanistic enzymology, • Structure-guided peptide design, • Structure-guided antibody design, • Fragment-based drug discovery, • Structure-based medicinal chemistry, • PhD or equivalent industry experience in drug discovery, medicinal chemistry, chemical biology, biochemistry, or a closely related field., • Strong understanding of drug discovery research methodologies and scientific evidence evaluation., • Ability to construct complex scientific problems with defensible conclusions., • Strong analytical and critical-thinking skills., • Ability to evaluate scientific reasoning quality, not simply final answers., • Strong scientific writing and documentation skills., • Comfortable working independently in a remote research environment., • Ability to commit at least 20 hours per week. Preferred Qualifications • Experience designing or evaluating drug discovery research strategies., • Strong background in structure-based drug design, protein–ligand interactions, enzymology, or molecular discovery., • Experience working with scientific literature, experimental datasets, structural data, and research documentation., • Experience developing research assessments, scientific benchmarks, or evaluation frameworks., • Familiarity with open-source scientific tooling and computational research workflows., • Experience evaluating AI-generated scientific research or technical outputs is a plus., • Strong ability to distinguish defensible scientific conclusions from unsupported assumptions or superficial reasoning. Compensation • Competitive compensation of $60–$90/hour., • Hourly contract engagement., • Fully remote., • Minimum commitment: 20 hours/week., • Up to 40 hours/week available., • Claude Max subscription required for the project and fully reimbursed., • Work conducted through a browser-based research studio and Claude Code. Application Process • Apply to the role, • Complete the required screening questions, • Provide details about your drug discovery and scientific research experience, • Complete the relevant scientific assessment, • Participate in the evaluation/interview stage, • Complete onboarding and tooling setup, • Begin designing and evaluating drug discovery research tasks

Drug Discovery Scientist Position: Drug Discovery Scientist Type: Hourly Contract Compensation: $60–$90/hour Location: Remote About the Opportunity This opportunity is for experienced Drug Discovery Scientists to contribute to an advanced AI research and evaluation project focused on pharmaceutical research and development. You'll apply your scientific expertise to design realistic, evidence-driven drug discovery problems that require AI models to reason through incomplete, indirect, and potentially misleading scientific evidence. You'll create research prompts, build supporting data rooms using real source-grounded information, develop rigorous grading frameworks, and validate the resulting tasks. The role is ideal for experts who can distinguish genuine scientific reasoning from pattern matching and confidently evaluate the quality of complex research conclusions. Responsibilities • Design challenging, realistic drug discovery research problems based on authentic scientific workflows., • Develop research scenarios where the correct conclusion must be derived from multiple pieces of evidence rather than directly stated., • Build comprehensive data rooms using real, source-grounded scientific data and documentation., • Ensure every decisive scientific value and piece of evidence can be traced back to a reliable source., • Create detailed grading documents and evaluation rubrics that assess scientific reasoning and substantive conclusions., • Evaluate AI-generated research outputs for scientific accuracy, logical consistency, and defensibility., • Run verification and calibration processes to ensure tasks are reproducible, appropriately difficult, and objectively scorable., • Identify weaknesses in task design, evidence, or evaluation criteria and revise them accordingly., • Provide expert judgment on scientific questions, task difficulty, and the quality of AI reasoning., • Collaborate with project reviewers and other domain experts to refine research tasks. Required Qualifications • Professional expertise in one or more of the following areas:, • Mechanistic enzymology, • Structure-guided peptide design, • Structure-guided antibody design, • Fragment-based drug discovery, • Structure-based medicinal chemistry, • PhD or equivalent industry experience in drug discovery, medicinal chemistry, chemical biology, biochemistry, or a closely related field., • Strong understanding of drug discovery research methodologies and scientific evidence evaluation., • Ability to construct complex scientific problems with defensible conclusions., • Strong analytical and critical-thinking skills., • Ability to evaluate scientific reasoning quality, not simply final answers., • Strong scientific writing and documentation skills., • Comfortable working independently in a remote research environment., • Ability to commit at least 20 hours per week. Preferred Qualifications • Experience designing or evaluating drug discovery research strategies., • Strong background in structure-based drug design, protein–ligand interactions, enzymology, or molecular discovery., • Experience working with scientific literature, experimental datasets, structural data, and research documentation., • Experience developing research assessments, scientific benchmarks, or evaluation frameworks., • Familiarity with open-source scientific tooling and computational research workflows., • Experience evaluating AI-generated scientific research or technical outputs is a plus., • Strong ability to distinguish defensible scientific conclusions from unsupported assumptions or superficial reasoning. Compensation • Competitive compensation of $60–$90/hour., • Hourly contract engagement., • Fully remote., • Minimum commitment: 20 hours/week., • Up to 40 hours/week available., • Claude Max subscription required for the project and fully reimbursed., • Work conducted through a browser-based research studio and Claude Code. Application Process • Apply to the role, • Complete the required screening questions, • Provide details about your drug discovery and scientific research experience, • Complete the relevant scientific assessment, • Participate in the evaluation/interview stage, • Complete onboarding and tooling setup, • Begin designing and evaluating drug discovery research tasks

A successful Associate Research Scientist typically advances to Research Scientist in one to three years. Manage qualitative data in qualitative data analysis software, including transcript preparation, codebook development, and coding. The Associate Research Scientist specializes in implementation

People Analytics & Research is a strong team of Data Scientists, Data Engineers, and Analysts. We need a Data Scientist with a proven track record of translating data into insight and action. The People Analytics & Research team is looking for an experienced Data Scientist to lead and/or contribute

We are looking for a Staff Data Scientist to join our Safety Insights Data Science team. In this role, you will partner closely with Safety Product, Engineering, and Machine Learning teams along with fellow Safety data scientists, to shape strategy, product development, define and evolve safety metr

We are looking for a Senior Data Scientist to join Safety Enforcement Data Science. Safety & Mods Data Science operates as a closed-loop system: Safety Insights helps the organization understand, measure, and prioritize risk, while Safety Enforcement Data Science builds and optimizes the models, rul

Leadership in data science: experience leading cross-functional teams of data scientists, data engineers, and data or cost analysts, and defining a data strategy aligned to organizational goals. Knowledge and experience performing cost estimating and analysis on major defense systems, including typi

Senior Data Scientist - Measurement. As an AI Engineering team member, you will have the opportunity to leverage cutting-edge data science, machine learning and AI on petabytes of data in ways that make a large and lasting impact on the company. Your daily Impact as Senior Data Scientist.

Your daily Impact as Data Scientist. As an AI Engineering team member, you will have the opportunity to leverage cutting-edge data science, machine learning and AI on petabytes of data in ways that make a large and lasting impact on the company. Explore our data and systems, prototype ideas, run exp

About Sapio Sciences Sapio Sciences is on a mission to accelerate scientific drug discovery and high-throughput clinical and diagnostics for our clients and partners. The Sapio team consists of expert and highly collaborative scientists, software developers, and professionals passionate about providing a best-in-class lab informatics platform and industry-specific solutions. Sapio is one of the few software providers to offer a truly unified and highly configurable lab informatics platform and a broad suite of purpose-built solutions. The Sapio platform makes it easy for scientists, laboratory, and bio/informatics professionals to streamline and manage their end-to-end laboratory operations, from instrument data integration to workflow and experiment setup to sample and materials management, data management, and scientific data analysis and reporting. Working at Sapio At Sapio, we’re not just building lab informatics solutions. We’re creating tools made for the scientist and motivated to make the world a better place. We understand that lab informatics is about more than managing data or connecting workflows. It’s about making life easier for the scientist and making scientific progress faster for everyone. Our platform delivers the levels of configurability, usability and insight that scientists have only ever dreamed of. We’re a team of scientists, developers and innovators who question convention and stay focused on what matters most - advancing drug discovery science. We challenge the status quo and respond to the needs at the heart of science with powerful solutions that are simple to use, effortless to evolve and downright easy to love. As part of the Sapio team, you’ll work in a collaborative and forward-thinking environment where your ideas are valued, your growth matters and your work makes a difference. We’re proud to partner with leading labs around the world, from ambitious start-ups to global organisations, who trust Sapio to support discovery, development and diagnostics with industry-first science-aware solutions. Position Summary Sapio Sciences is looking for a Director of Field Marketing to own our global events strategy across the UK, Europe, and North America. This is a high-impact, hands-on role for someone who thrives at the intersection of strategy and execution — from selecting the right tradeshows and industry conferences to designing the booth, managing the budget, and turning attendee lists into pipeline. You'll run webinar programs end-to-end, partner closely with Product Marketing, Commercial Partnerships, and Sales to ensure every event drives measurable ROI, and build the team and processes needed to scale field marketing as we grow. Essential Responsibilities • Own the end-to-end events calendar across UK, Europe, and North America, including tradeshows, industry conferences, webinars, and field/regional events from selection through post-event reporting, • Communicate field marketing strategy, planned programs, and expected outcomes to the broader team on a regular cadence, • Manage all event logistics: booth design and build, shipping, staffing, vendor contracts, lead capture setup, and on-site execution, • Plan and run webinar programs, including topic selection, speaker coordination, promotion, and post-event follow-up sequencing with Marketing, • Build and manage event budgets; negotiate with venues, booth vendors, and sponsors to maximize ROI, • Partner with Product Marketing to ensure event messaging, collateral, and demos reflect current positioning and active launches, • Partner with the Director of Commercial Partnerships to align event objectives with partner marketing strategies and co-marketing initiatives, • Coordinate with Sales on target account lists and pre-event outreach so tradeshow attendance converts to pipeline, • Manage relationships with industry associations and conference organizers (e.g. SLAS, Bio-IT World, and similar life sciences and informatics events), • Track and report on event performance, leads generated, pipeline influenced, cost per lead, ROI and post event reports to apply findings that shape the forward calendar, • Manage and develop event coordinators, contractors, and agency partners supporting field programs, • Train booth staff on event etiquette, lead capture best practices, and on-site messaging consistency, • Travel on-site to run events in person across all regions as needed; estimated at 20% of time Required Education & Experience • 5+ years in B2B field marketing or event marketing, • Proven track record running tradeshow programs end-to-end, including budget ownership, vendor negotiation and ARR contribution, • Experience running webinar and virtual event programs on with such tools as Go To Webinar, Zoom, etc, • Comfortable working across UK, EMEA and US time zones and travel logistics, • Very strong project management skills using tools like Asana, Trello, where you can run multiple events in parallel without dropping details, • Experience working with CRM/marketing automation platforms (HubSpot preferred) for lead capture, tracking, and reporting, • Clear, direct communicator who can work cross-functionally with Sales, Product Marketing, and executive stakeholders, • Strong preference to candidates with SAAS (software as a service) experience, • Nice to have: Existing familiarity with life sciences, laboratory informatics, LIMS, or regulated lab markets Our People At Sapio Sciences, our people are at the heart of everything we do. Our lab informatics solutions are powered not just by technology, but by a shared commitment to our core values—what we proudly call The Sapio Seven, aka EMBRACE: • Embrace the future • Make a difference • Be true partners • Remember why we’re here • Act with empathy • Commit to transparency • Excel in quality These values shape how we work, how we grow, and how we deliver impact for our clients every day. Reasonable Adjustments We are committed to ensuring an inclusive and accessible recruitment process. If you require any reasonable adjustments, at any stage across the application, interview & assessment processes then please let us know. We will work with you to support your needs in confidence. Diversity, Equity & Inclusion We do not discriminate based on race, colour, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, or any other status protected by law or regulation. We intend that all qualified applicants be given equal opportunity and that selection decisions are based on job-related factors. We are committed to creating a diverse and inclusive workplace and encourage applications from all qualified individuals. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.

If you are a scientist who wants your training to directly influence how new devices reach patients—and you are willing to learn fast, write well, and grow with a small team—this is a strong entry point into a long‑term regulatory affairs career. About the role Mittal Consulting partners with innovative medical device companies to help them bring safe, effective technologies to patients worldwide through precise, timely regulatory strategy and submissions. This role is an opportunity to translate deep scientific training into real‑world impact by shaping how novel Class II and III devices reach US and global markets. It is designed for someone who prefers ownership and mastery over complex problems, and who values mentorship, clarity, and long‑term collaboration. What you will do • Build and refine practical regulatory tools, templates, and processes for medical device submissions (US and EU), helping make complex requirements understandable and repeatable for clients., • Draft, organize, and quality‑check key regulatory documents (e.g., Q-Subs, 510(k), De Novo, PMA, technical files, design dossiers) with a focus on logic, narrative flow, and scientific accuracy rather than “filling out forms.”, • Learn to map product concepts and scientific data to appropriate US, EU, and international regulatory pathways and risk classifications., • Maintain submission planners, timelines, and logs, so projects move forward reliably, and clients experience a calm, organized process even when their science is fast‑moving., • Participate in the preparation of FDA interactions (e.g., pre‑subs, meeting requests, responses to questions) and help distill technical input into concise, defensible positions., • Gradually take on more client‑facing and project management responsibility as you demonstrate judgment, reliability, and strong written work. Who will thrive here This role is ideal for a recent PhD/Post‑Doc graduate in engineering, biomedical, or hard sciences who wants to pivot from pure research into regulatory and strategy work without giving up intellectual challenge. You are likely to enjoy this if you: • Learn new frameworks quickly and enjoy going from “I’ve never seen this” to “I can explain this clearly” in a short time., • Have a low‑ego, ownership mindset: you care more about getting it right than being right, take editorial feedback well, and are willing to iterate your work product., • Write clearly, succinctly, and logically; you are comfortable turning scattered inputs (emails, reports, data) into coherent, well‑structured documents., • Prefer depth over title: you want to become a trusted regulatory thinker over time, not just “check a box” to get experience., • Value loyalty and long‑term collaboration and are looking for a place where investing in the relationship is reciprocated with mentorship, flexibility, and increasing responsibility. Qualifications and working conditions • PhD or Post‑Doctoral training in engineering, neuroscience, biomedical sciences, or a closely related hard science; prior exposure to medical devices or clinical/regulated environments is a plus but not required. Pharma background is not ideal., • Demonstrated excellence in scientific or technical writing (e.g., manuscripts, grant sections, white papers, protocols) and careful document review., • Strong organizational habits, comfort managing multiple workstreams, and responsiveness to deadlines., • Interest in developing expertise in FDA and EU medical device regulations, including 510(k), De Novo, and PMA pathways, with guidance and training., • Remote, flexible‑hours 1099 contractor role; you provide your own workspace and laptop, and work software (email, Zoom, Office, CRM) is provided as needed., • Headquarters in Portland, Oregon; occasional reimbursed travel may be required for select meetings or client needs, (e.g traveling to Washington D.C for meetings with the FDA) See what is it like to work at Mittal Consulting https://www.youtube.com/watch?v=F6LxNnTV8&t=204s

Founding AI Scientist - Pathology Foundation Models Remote (Must be US Based) The Role You will lead the strategy and development of pathology foundation models, shaping how they are designed, trained, evaluated, and deployed into clinical and pharmaceutical applications. This is a highly cross-functional role spanning research and production. You will define how foundation models integrate with biological context, multimodal data, and downstream decision-making systems moving beyond isolated model improvements to building end-to-end, real-world solutions. As an early-stage hire, you will play a key role in shaping both the technical direction and the organisation itself. Required Experience • Strong publication record in machine learning, including multiple first-author papers at leading conferences or journals, • Deep understanding of modern ML architectures (e.g. transformers, attention mechanisms, state-space models, mixture-of-experts), • Experience working with GPU clusters and large-scale ML infrastructure (e.g. Kubernetes, SLURM, or similar), • Solid software engineering skills and ability to build production-grade systems, • Excellent communication skills, with the ability to convey complex ideas to both technical and scientific audiences Preferred Background • Experience in oncology, cancer biology, or drug development, • Exposure to biomedical or healthcare foundation models, • Experience with multimodal and cross-modal learning systems, • Familiarity with healthcare regulatory frameworks (e.g. FDA, HIPAA), • Contributions to open-source ML ecosystems, • Experience working with distributed or community-driven research groups, • Previous experience in a startup or early-stage environment To apply please reach out to Sam Shinner at Discover International

Scope: We are hiring a pioneering, fully autonomous Lead Data Scientist to own the complete data science lifecycle for our flagship prediction model project. This role is mission-critical — the candidate will be the single point of expertise responsible for sourcing, analyzing, and engineering all data that powers our predictive models. Operating independently with minimal supervision, this individual must combine deep AI/ML mastery, hands-on engineering skills, and sharp business acumen to deliver measurable, production-grade outcomes. Key Responsibilities: Data Analysis & Pipeline Ownership ▸ Lead end-to-end analysis of large, complex, multi-source datasets to surface patterns driving model inputs ▸ Identify, collect, clean, validate, and transform all data required for prediction model consumption ▸ Design and maintain scalable, production-grade data pipelines (training, validation, inference) ▸ Perform deep EDA, data profiling, and quality audits to ensure model-ready data standards Predictive Modeling & AI/ML ▸ Architect, train, evaluate, and iterate ML models — supervised, unsupervised, and reinforcement learning ▸ Own feature engineering: selection, extraction, transformation, and dimensionality reduction ▸ Apply advanced techniques: deep learning, NLP, time-series forecasting, ensemble methods ▸ Benchmark, A/B test, and monitor models in production; drive continuous performance improvement ▸ Deploy models via REST APIs (FastAPI/Flask); ensure reproducibility and scalability Independent Ownership & Leadership ▸ Self-direct from problem definition through solution delivery with zero hand-holding ▸ Translate ambiguous business problems into precise, executable data science problem statements ▸ Communicate model results and data insights clearly to technical and non-technical stakeholders ▸ Document all experiments, methodologies, and outcomes — audit-ready and reproducible ▸ Champion best practices across the data science lifecycle; mentor junior team members QUALIFICATIONS ▸ B.S./M.S./Ph.D. in Computer Science, Statistics, Mathematics, or equivalent quantitative field (Master's/Ph.D. strongly preferred) ▸ 5+ years of hands-on data science experience with at least 2 years delivering production-grade ML models ▸ Proven ability to own and deliver end-to-end data science projects independently ▸ Portfolio demonstrating innovation in predictive modeling and measurable business impact ▸ Experience in a fast-paced, data-driven, decision-model environment REQUIRED SKILLS & QUALIFICATIONS Core Data Science & Mathematics ▸ Statistics (Bayesian inference, hypothesis testing, regression, distributions) ▸ Linear algebra, calculus, and probability applied to ML model design ▸ Supervised & unsupervised learning, anomaly detection, clustering ▸ Time-series analysis & forecasting: ARIMA, Prophet, LSTM Programming & Development ▸ Python (Expert): NumPy, Pandas, Scikit-learn, Statsmodels, Matplotlib, Plotly ▸ SQL (Advanced): window functions, CTEs, query optimization ▸ Git / GitHub; CI/CD for ML; MLOps with MLflow or Kubeflow ▸ Docker & Kubernetes for model containerization and serving AI / ML Frameworks (Must-Have) ▸ TensorFlow and/or PyTorch — deep learning architectures ▸ XGBoost, LightGBM, CatBoost — gradient boosting & ensemble methods ▸ Hugging Face Transformers — NLP, LLMs, and fine-tuning ▸ SHAP, LIME — model explainability and interpretability ▸ LLMs / Generative AI / Prompt Engineering — strong advantage Cloud & Data Infrastructure ▸ AWS (SageMaker, S3, Glue), GCP (Vertex AI, BigQuery), or Azure ML ▸ Apache Spark / PySpark — distributed data processing ▸ Airflow / Prefect — pipeline orchestration Snowflake (Good to Have) ▸ Snowflake Data Cloud: querying, Snowpark for Python ML pipelines ▸ Snowflake Cortex AI / ML Functions for in-database ML ▸ dbt for data transformation; data governance within Snowflake

Our client, a major legal company, is actively looking for a Senior Data Scientist to join their team! This is a fully remote position, however candidates must be located in the US and able to work EST hours. We are seeking a Data Scientist to develop and evaluate AI solutions for legal content work

Our client seeks a Principal Data Scientist to scale Data Science and AI capabilities for end-to-end payment optimization. Foster a culture of innovation, experimentation, and collaboration while mentoring an elite team of data scientists. Collaborate with Data Science leaders to establish an operat

Optimize and automate data pipelines using Python, PySpark, and R, ensuring efficient data processing and feature engineering. Mentor and guide junior data scientists, fostering technical excellence and continuous learning within the team. Relevant certifications in machine learning, statistical ana

This role will work across both Data Science and Data Engineering, with a focus on analyzing operational data, developing performance benchmarks, maintaining dashboards, and troubleshooting vendor-facing data challenges. Data Science, Data Analytics, Analytics Engineering, Data Engineering, or a rel

Company Description RP-IO helps organizations hire and scale more efficiently. We are actively recruiting for a Senior Data Scientist for a Contract, remote position, for one of our customers based in the Bay Area. Why This Role Exists Our client (Company) is integrating with another company (Parent Company - PC). The PC is taking over Company's prospect account scoring in stages and folding in its own marketing, outbound, pre-approval, and credit models. It is building the replacement models on their current data. Until that finishes, their production scoring system still decides which accounts outbound reps work. Over the engagement, their systems will increasingly run on PC's scores instead. This role runs the transition end to end. It hands PC the Company's training data, validates PC's scores against Company's, integrates and applies those scores in Company's sales targeting, and keeps the current system healthy until cutover. It is one project with a defined end. It also frees the data scientist who built the system for other work, so the hire must run with little handholding after a roughly 6-week ramp. What You Inherit • Three supervised models on tabular data. A value model (CatBoost regression on expected spend), an intent model (survival model on time to first meeting), and an outreach model (calibrated contact-level classifier rolled up to the account). They blend into a 0-100 prospect score., • A weekly batch pipeline. Features are SQL on Snowflake. Models train and score on AWS SageMaker. dbt assembles point-in-time score history and applies eligibility rules., • A live business use. The score drives the quarterly assignment of prospect accounts to outbound reps' fixed books, and reps use it to prioritize within their books., • An explainable signal-tier layer. A daily tier that tells a rep which accounts are showing intent right now and names the reason. It is rolling out with RevOps., • An earlier handoff. Company has already shared a model validation dataset with PC's data science team., • Tools. Python, SQL, Snowflake, dbt, SageMaker, Hex, Salesforce, GitHub, Linear. What You'll Do • Run and maintain the scoring system. Own the weekly scoring runs, monitoring, data-quality fixes, and documentation. Support the lightweight November 2026 fixed-book refresh and the major January 2027 refresh., • Build the training data for PC's models. PC is building models for company's prospect targeting, trained on company data. This is the current project. Assemble and hand over the training sets: account history, Company-specific features, and outcome labels such as meetings, conversions, and spend. Make them point-in-time correct, with documented definitions, label rules, and known biases, including outreach that the existing score directed. Define labels the same way Company's own models do, so the two can be compared later., • Validate PC's scores on Company data. Test whether PC's scores give lift over Company's existing scores on Company outcomes. Keep the test honest by using accounts or time periods PC's models never trained on, usually out of time. Measure lift at the cutoff reps actually work, by segment, along with calibration and coverage. Give a clear recommendation to switch, blend, or hold. This read gates the cutover., • Lead the integration of PC's scores into Company. Data moves in both directions. PC will deliver its scores to Company, through a scheduled drop into Snowflake or through an API. Company may also need to send PC a recurring 5. 6. 7. 8. feed of Company-specific features for scoring, through a data share, a scheduled job, or a Company-side API. The interface is not designed yet. You lead the data science side end to end: requirements, feature definitions, the data contract with PC's team, validation of what comes back, monitoring, and cutover. Make sure incoming scores are stored with as-of dates so any past score can be reconstructed. Data Engineering and Company's engineering build the pipelines and any API. You write the data specs and validate the result., • Apply PC's scores in sales targeting. Start with PC's prospect risk score. With the technical lead, test whether it works better as an eligibility filter or as a ranking input, given how many accounts the books need. Implement the chosen path in the book-assignment tool behind a configuration switch. Design the control group for the January refresh and deliver the readout on approvals, conversion, and activation. The live test confirms what the offline validation predicts., • Be PC's working counterpart on scoring. Answer their data science team's questions about Company's models, data, and business. Keep Company's model documentation current. Field targeting-related data requests from PC and RevOps through the data team's PC request process., • Help get data approvals. Work with the hiring manager and the technical lead on Company's Legal, Compliance, and Trust reviews of data exchanged with PC, starting with the training data, and on model risk questions from PC. Write the use-case and data-handling summaries reviewers need, answer their questions, and track each approval to closure. So far this has been light work., • Project-manage the transition. Keep the plan, milestones, and decision log. Run the working cadence across PC, RevOps, and Data Engineering, and raise blockers early. Write the plan to retire Company's models and hand off what remains. Out of Scope • New model development. PC builds the replacement models. Retrains and fixes that keep Company's current models healthy are in scope., • ML engineering. Data Engineering and Company engineering build and own pipelines, APIs, serving infrastructure, and every data share with PC. You specify and validate., • Sales policy. RevOps decides book design and sales process. You supply the analysis., • Unapproved data use. Today, PC scores enter targeting as delivered attributes, not as training features in Company models. Every data exchange with PC, in either direction, goes through Company's approval path. That includes Legal review of which Company data can be shared. Requirements • 5+ years in data science, including owning production ML models end to end: build, deploy, monitor, retrain., • Supervised ML on tabular data, especially gradient-boosted trees. Survival or time-to-event modeling is a plus.-, • Strong SQL and Python. Snowflake and dbt preferred., • Has run batch scoring pipelines in production on SageMaker or an equivalent platform., • Has used an external partner's data or model scores in production, including data contracts, validation, and monitoring. Snowflake data sharing preferred., • Has built model training datasets: point-in-time features, label definitions, and leakage control., • Rigorous model evaluation: ranking metrics, calibration, point-in-time correctness, leakage, and bias from outreach that the score itself directed., • Has evaluated a vendor or partner model against an in-house baseline on held-out data., • Experiment design in an operating business: control groups, power, and readouts that decision-makers act on., • Lead or account scoring, sales targeting, or territory design in B2B, including Salesforce data., • Works directly with an external partner's technical team and with senior RevOps stakeholders. Writes clear documentation., • Runs a multi-team project without a dedicated project manager., • MS or PhD in a quantitative field, or equivalent production experience. Bonus • Fintech, card, or credit risk experience, especially using a third-party risk or credit score in targeting., • Has taken a data-sharing or model-use case through legal, compliance, privacy, or a bank's model risk review., • Experience with a feature store. Company uses Chalk. What We Screen For • Applied ML data scientist, not an ML engineer. Strong on modeling, evaluation, and getting model output used in the business. Engineering builds the infrastructure., • Ownership, not ticket execution. Figures out what the problem is and drives it without waiting for a spec., • Production depth. Has kept a model running in production and dealt with what broke. Research-only profiles don't fit., • Partner-facing judgment. Can tell an external team plainly what a model can andccan't support, and tell Company plainly when a partner's model doesn't beat ours.

We're looking for a Junior Data Scientist to join a growing analytics team focused on building data-driven solutions and improving business performance through modern technologies. Contribute to the maintenance and optimization of data models and pipelines. Understanding of cloud-based analytics or

Junior Data Scientist Position: Junior Data Scientist Type: Contractor Compensation: $150–$200/hour Location: Remote About the Opportunity We are seeking Data Scientists and Quantitative Professionals with experience at leading organizations to support an AI research project. You’ll evaluate AI model performance across statistics, machine learning, experimentation, and quantitative reasoning to help improve model accuracy and analytical capabilities. Key Responsibilities • Evaluate AI-generated outputs involving data science, statistics, machine learning, and quantitative problems., • Create challenging prompts, datasets, and reference solutions., • Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning., • Assess data analysis, experimentation approaches, and data modeling techniques., • Provide structured, actionable feedback to improve AI model performance. Required Qualifications • At least 1 year of experience at a leading company in technology, finance, research, or a related field, with some experience within the past 3 years., • Strong understanding of Python, statistics, machine learning, and data analysis., • Experience with Pandas, data modeling, and experimentation., • Strong analytical and quantitative reasoning skills., • Ability to communicate technical and statistical concepts clearly in writing., • Based in an English-speaking country. Preferred Qualifications • Experience evaluating statistical models, machine learning outputs, or quantitative methods., • Strong knowledge of experimental design, data interpretation, and methodological validation., • Ability to develop rigorous datasets and reference solutions for complex analytical problems. Compensation • $150–$200/hour., • Independent contractor engagement., • Fully remote work., • Approximately 100 openings available. Application Process • Submit your application with relevant data science or quantitative experience., • Complete any required screening or technical evaluation., • Demonstrate your statistical reasoning and analytical skills., • Begin evaluating AI outputs and developing data science tasks if selected.

As Scientist / Lead, Translational Data Platforms, you will play a pivotal role in shaping how researchers interact with complex clinical and multi-omic datasets, influencing platform strategy, developing innovative analytical capabilities, and helping build technologies that enable the next generat

Position: Data Scientist | AI & ML Analyst. Data Scientist | AI & Machine Learning. Data Scientist | AI & Machine Learning.

In this role, you will analyze large-scale utility datasets, evaluate customer-facing digital products (such as rate recommendation and bill comparison tools), and build interactive reporting tools to drive business decisions and improve customer experience. Partner closely with Product Owners, soft

Strong communication skills to suit a highly-collaborative fast-paced remote work environment.

About the Company We are an international academic and technology exchange platform dedicated to fostering global research and innovation. Working with world-leading universities, institutes, and listed companies, we host international programs, conferences, and academic events to attract top scholars worldwide. Our mission is to build competitive research teams and accelerate cross-border knowledge, technology, and talent exchange, driving scientific advancement across disciplines. About the Role You have the autonomy to select your laboratory and hold absolute authority over it. Opportunity to establish your own research group and grow into a Young PI. Full support for international collaborations, academic conferences, and project partnerships. Responsibilities • You have the autonomy to select your laboratory and hold absolute authority over it., • Opportunity to establish your own research group and grow into a Young PI., • Full support for international collaborations, academic conferences, and project partnerships. Qualifications • PhD degree from a globally recognized university or leading research institute, • Strong academic background with proven independent research capability, • Demonstrated record of high-quality publications or project leadership, • Willingness to collaborate with Chinese academic or industrial partners, • Open to outstanding applicants of all nationalities Required Skills • STEM or related applied disciplines, • International research, industry, or innovation experience, • Expertise aligned with strategic areas such as:, • New energy and green technologies, • Advanced materials and manufacturing, • Biomedicine and life sciences, • Artificial intelligence, data science, digital technologies, • Semiconductor and high-end equipment, • Open to all nationalities, • No geographic relocation requirement Preferred Skills • Strong academic background with proven independent research capability, • Demonstrated record of high-quality publications or project leadership, • Willingness to collaborate with Chinese academic or industrial partners Pay range and compensation package • Annual Salary: USD 200,000 – 300,000+ (negotiable based on qualifications), • Research Startup Funding: up to USD 400,000, • Housing & Settlement Support: up to USD 400,000 (talent housing, rental subsidies, or property purchase assistance), • Additional Support:, • Comprehensive “one-stop” onboarding and long-term service support, • Career Development Opportunities, • Clear promotion path: Scientist → Senior Scientist Equal Opportunity Statement Open to outstanding applicants of all nationalities. We are committed to fostering an inclusive environment that values diversity and supports equal opportunity for all individuals regardless of nationality or background.

How You’ll Make An Impact • We are looking for a candidate to join our Commercial Analytics and Data Science team. We are seeking a person that applies strong programming and statistical skills to experimentation and machine learning model development., • This position plays a key role in optimizing media spend through building marketing mix models and designing and measuring incrementality tests. You will also support test design and evaluation of marketing initiatives across multiple channels spanning the customer lifecycle. A keen interest and ability to advance organizational capabilities through research and innovation initiatives across areas such as AI, causal inference, and experimentation is critical. Responsibilities What you’ll do: • Build marketing mix models to estimate incremental ROI of marketing channels and optimize spend. Experience using tools such as Robyn and Meridian is preferred., • Design and measure paid media incrementality tests using geo-experiments, • Support testing marketing initiatives to drive app engagement and increase subscriber retention across the customer lifecycle applying proper statistical rigor. Responsibilities include experimental design (sample sizing, timing), quality checking implementation, and test measurement and evaluation., • Build machine learning models for predicting key outcomes used to inform marketing tactics across digital acquisition and user journey orchestration, • Build web applications using Python providing daily monitoring of test results and model results and insights, • Deliver presentations describing experimental results and recommendations to business partners, • Work closely with engineering to productionize and monitor model performance, • Contribute to research and innovation initiatives to further organizational capabilities across AI, causal inference, and statistical methods, • Represent Commercial Analytics and Data Science capabilities and deliver data-driven insights within cross-functional teams to help achieve business objectives, • Develop complex SQL queries combining data from a wide variety of sources in preparation of feature engineering and test analysis, • Create custom Python libraries available for team use to automate key methods Requirements What you’ll need: • Bachelor’s or Master's degree in data science, computer science, statistics, engineering, or related quantitative field., • 5 or more years of experience as a Data Scientist, • Background in paid media, ideally with experience at large media companies, • Experience building Marketing Mix Modeling (MMM) models, • Experience with paid media incrementality measurement/testing, • Strong foundation in SQL, • Understanding or experience working within an enterprise data warehouse environment, • Experience working in or partnering with media agencies, • Background in subscription or e-commerce businesses, • Experience building web apps using frameworks such as Streamlit, Shiny, or Dash is preferred, • Capability to build, tune and explain machine learning models for supervised and unsupervised learning. Methods include, but are not limited to, regression, clustering, and ensemble methods., • Understanding of statistical concepts, lift analysis, and A/B testing fundamentals, • Ability to produce data visualizations for explaining technical concepts, • Experience with cloud technologies, • Familiarity with business intelligence dashboards Compensation • $64.52 to $93.55/hr. (W2), • Dependent upon location* Job req# 3056-1

Job Type: Flexible Contract (Remote) Cobalt is hiring experienced biologists to review and build tasks that test whether frontier AI models can reason through real experimental science. Your job is to judge whether a model’s reasoning about an experiment is correct, and to explain precisely where it goes wrong when it is not. We are especially looking for scientists with hands-on flow cytometry experience. If you are the person in your lab who spots the flawed control, the mislabeled gate, or the conclusion the data does not support, this role is built around that skill. What you will do • Review AI-generated answers to experimental biology problems end to end, including the experimental design, the methods, the data interpretation, and the final conclusion, and confirm that each step is scientifically sound and consistent with the others., • Write realistic problems from your own area of expertise, along with reference solutions that show the reasoning a skilled scientist would follow, not only the final answer., • Look for ways a model could reach a correct-looking answer without sound reasoning, such as relying on a textbook pattern that does not fit the data, ignoring a missing control, or overlooking an artifact, and document each issue clearly., • Judge whether a model’s failure reflects a real gap in scientific reasoning, or instead reflects an ambiguous question, missing information, or an unfair reference answer., • Write clear, specific feedback and work with task authors through revisions until each task meets the acceptance standard., • Join occasional expert calls of 30 to 60 minutes with research teams who want to understand how experts approach a specific problem. Example tasks you might review include designing a multicolor flow cytometry panel for a given set of markers and instrument, critiquing a gating strategy and identifying where a population was misassigned, explaining why compensation errors produced a false double-positive population, and judging whether a reported difference between treatment groups is supported by the data. Who we are looking for • PhD in biology, immunology, cell biology, biochemistry, or a closely related life sciences field., • Hands-on laboratory experience, gained through research, a thesis, a postdoctoral position, a core facility, or industry work. You should be comfortable reading an experimental protocol and saying whether it would work., • Strong working knowledge of experimental design, including controls, replicates, and when a difference between two results is meaningful., • Careful, direct written communication. Much of the job is explaining precisely what is wrong and why., • No prior experience with AI is required. Strong advantages • Hands-on flow cytometry experience, including panel design, compensation, gating, and data analysis, using instruments such as the BD FACSymphony or Cytek Aurora and software such as FlowJo, FCS Express, or OMIQ., • Experience with spectral or mass cytometry, or with clinical flow cytometry such as leukemia and lymphoma immunophenotyping., • Experience managing or working in a core facility, training other scientists, or serving as a peer reviewer for a journal. Why Cobalt AI • Shape how AI understands science. Your judgment directly determines which tasks are used to measure what leading models can and cannot do in biology., • Use your expertise in a new way. You will see up close how frontier models reason about experiments and where they break., • Fit the work around your current role. Set your own schedule, with flexible weeks that can scale up or down around your research and other commitments., • Grow with us. Strong reviewers can move into task design, project leadership, and research collaborations on future projects.

Drug Discovery Scientist Position: Drug Discovery Scientist Type: Hourly Contract Compensation: $60–$90/hour Location: Remote About the Opportunity This opportunity is for experienced Drug Discovery Scientists to contribute to an advanced AI research and evaluation project focused on pharmaceutical research and development. You'll apply your scientific expertise to design realistic, evidence-driven drug discovery problems that require AI models to reason through incomplete, indirect, and potentially misleading scientific evidence. You'll create research prompts, build supporting data rooms using real source-grounded information, develop rigorous grading frameworks, and validate the resulting tasks. The role is ideal for experts who can distinguish genuine scientific reasoning from pattern matching and confidently evaluate the quality of complex research conclusions. Responsibilities • Design challenging, realistic drug discovery research problems based on authentic scientific workflows., • Develop research scenarios where the correct conclusion must be derived from multiple pieces of evidence rather than directly stated., • Build comprehensive data rooms using real, source-grounded scientific data and documentation., • Ensure every decisive scientific value and piece of evidence can be traced back to a reliable source., • Create detailed grading documents and evaluation rubrics that assess scientific reasoning and substantive conclusions., • Evaluate AI-generated research outputs for scientific accuracy, logical consistency, and defensibility., • Run verification and calibration processes to ensure tasks are reproducible, appropriately difficult, and objectively scorable., • Identify weaknesses in task design, evidence, or evaluation criteria and revise them accordingly., • Provide expert judgment on scientific questions, task difficulty, and the quality of AI reasoning., • Collaborate with project reviewers and other domain experts to refine research tasks. Required Qualifications • Professional expertise in one or more of the following areas:, • Mechanistic enzymology, • Structure-guided peptide design, • Structure-guided antibody design, • Fragment-based drug discovery, • Structure-based medicinal chemistry, • PhD or equivalent industry experience in drug discovery, medicinal chemistry, chemical biology, biochemistry, or a closely related field., • Strong understanding of drug discovery research methodologies and scientific evidence evaluation., • Ability to construct complex scientific problems with defensible conclusions., • Strong analytical and critical-thinking skills., • Ability to evaluate scientific reasoning quality, not simply final answers., • Strong scientific writing and documentation skills., • Comfortable working independently in a remote research environment., • Ability to commit at least 20 hours per week. Preferred Qualifications • Experience designing or evaluating drug discovery research strategies., • Strong background in structure-based drug design, protein–ligand interactions, enzymology, or molecular discovery., • Experience working with scientific literature, experimental datasets, structural data, and research documentation., • Experience developing research assessments, scientific benchmarks, or evaluation frameworks., • Familiarity with open-source scientific tooling and computational research workflows., • Experience evaluating AI-generated scientific research or technical outputs is a plus., • Strong ability to distinguish defensible scientific conclusions from unsupported assumptions or superficial reasoning. Compensation • Competitive compensation of $60–$90/hour., • Hourly contract engagement., • Fully remote., • Minimum commitment: 20 hours/week., • Up to 40 hours/week available., • Claude Max subscription required for the project and fully reimbursed., • Work conducted through a browser-based research studio and Claude Code. Application Process • Apply to the role, • Complete the required screening questions, • Provide details about your drug discovery and scientific research experience, • Complete the relevant scientific assessment, • Participate in the evaluation/interview stage, • Complete onboarding and tooling setup, • Begin designing and evaluating drug discovery research tasks

Principal Data Scientist - Quantitative Intelligence. ML Scientist, Statistical Modeling, Predictive Modeling, Paneling, Normalization, Cohorting, Causal Inference, Synthetic Control, Uplift Modeling, Transaction Data, Behavioral Modeling, Forecasting, Representation Learning, Privacy Preserving ML,

Working closely with Marketing, Product, Finance, and Technology, the Senior Data Scientist transforms complex data into actionable insights that improve business performance in a highly competitive telecommunications environment. The Senior Data Scientist, Advanced Analytics, develops machine learn

Applied Scientist (Remote | $245–$280/hr) Position: Applied Scientist Type: Contractor Compensation: $245–$280 per hour Location: Remote About the Opportunity An AI-focused project is seeking Applied Scientists to contribute expertise in advanced analytics, experimentation, statistics, and machine learning. Contractors will help improve next-generation AI systems by evaluating model outputs, developing high-quality datasets, and providing expert feedback. Prior AI experience is not required. Key Responsibilities • Design and execute statistical analyses to uncover insights from complex datasets., • Develop, validate, and evaluate machine learning models for business and research objectives., • Apply data modeling techniques and manage data transformations using Python and Pandas., • Collaborate with stakeholders to establish experimentation frameworks and analyze outcomes., • Document methodologies, findings, and recommendations clearly and accurately., • Review peer contributions and provide constructive technical feedback., • Deliver reproducible code and organized analytical reports., • Evaluate AI model outputs involving statistics, machine learning, experimentation, and quantitative reasoning., • Create expert-level prompts, datasets, and reference solutions., • Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning., • Provide structured feedback to improve AI model performance. Required Qualifications • Strong proficiency in Python and data analysis., • Knowledge of machine learning, statistics, experimentation, and data modeling., • Experience with Pandas and related data science tools., • Strong analytical, problem-solving, and quantitative reasoning skills., • Excellent written and verbal communication skills. Preferred Qualifications • At least one year of experience at a leading company in technology, finance, or research., • Proficiency with Python libraries such as Pandas and scikit-learn., • Demonstrated experience in applied statistics, experimental design, and machine learning., • Experience developing, tuning, and evaluating machine learning models., • Ability to work with structured and unstructured data., • Experience collaborating on cross-functional or open data science projects., • Advanced academic background or practical experience in data science, applied mathematics, or a related field. Compensation • Hourly compensation of $245–$280., • Remote, contractor-based engagement. Application Process The application process was not specified in the provided listing.

Shopmonkey has the structured data and workflows to support serious data science work, and you'll have the rare opportunity to help build the analytical and ML foundation from the ground up, shaping how data-driven decision making scales alongside a maturing platform and defining what the future of

We are seeking a highly experienced and driven Senior Machine Learning Data Scientist to join our Women's Health team. You will play a pivotal role in developing and commercializing cutting-edge machine learning models and algorithms, leveraging wearable health data to improve women's health outcome

We are seeking an experienced AI Data Scientist to join Deltek’s growing AI Center of Excellence team to design, build, evaluate, and optimize enterprise AI solutions leveraging Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), multimodal AI, Opensource AI Models, and

Data Scientist (Live Anywhere). Proven track record of deploying models and data pipelines in cloud environments, preferably on GCP or other cloud platforms. Strong experience in data visualization tools (e.

You will work as a forward deployed data scientist: embedded with enterprise clients, turning ambiguous business problems into working analytical and AI solutions, and staying with the work until it runs in their environment. Strong practical data science skills, including working with messy enterpr

We are seeking a Data Scientist, Associate to build RoboStrategy’s data capability from the ground up. Bring together shareholder records, 13F filings, DTC position reports and allocator databases into a single view connected to our CRM, and use it to score, segment and prioritize investors, handl

We're hiring a Remote Data Scientist for a fast-growing, well-funded fintech company. This is a hands-on, non-client-facing seat on a small data team - you'll apply Python, SQL, and applied statistics/ML to real product and risk questions, working closely with engineers and analysts, and presenting

Principal Data Scientist, Quantitative Intelligence (Consumer Transaction Data). They’re hiring a Principal Data Scientist to be the hands-on technical lead for the team that turns this data into statistical methods and machine learning models. You’ll guide the work of several data scientists, w

You’ll join our Data team, report to our Head of Data, and help shape how data science is used across the company. Skool is hiring its first ever Data Scientist. Own data science work across growth, product, and user engagement, from analysis through measured results.

Outlier Experts work on a variety of projects, from generating training data to evaluating the performance of models. Additional incentives data is based on payments made in the past six months and is updated quarterly.

Product Testers are wanted to work from home nationwide in the US to fulfill upcoming contracts with national and international companies.We guarantee 15-25 hours per week with an hourly pay of between $25/hr.There is no payment required in order to apply or to work as an In-Home Usage Tester.You do