Trabajos data scientist en Springfield, MissouriCrear alertas

Job Description Since its inception, QPS has been assisting pharmaceutical, biotechnology and medical device companies with their drug development efforts by providing a full range of Neuropharmacology, DMPK, Toxicology, Bioanalysis, Translational Medicine, Early-Stage Clinical and Phase I IV Clinical Research services. We welcome individuals who want to be part of our growing organization. QPS is an innovative, dynamic organization that strives to employ talented, caring and committed employees who will work collaboratively towards achieving our mission of improving human health and the quality of life. QPS offers challenging and rewarding work in its four core business areas and support functions. Underpinning the operation is a culture that values diversity, innovation and accountability. Employees are encouraged to take responsibility and achieve their best, both as individuals and as team members. Description: The Medical Technologist (MT) performs a wide range of diagnostic testing, while bringing forth the specialized scientific and technical knowledge essential to perform most analytical testing in the Clinical Laboratory. The scope of testing is limited by specialty education and licensing requirements (i.e., cytotechnologist). They are responsible for the interpretation and reporting of lab tests, advanced troubleshooting, maintenance, problem resolution, and assessing specimen quality and test validity. A high level of technical skill is required for testing methods/systems, in which quality control materials and/or external proficiency testing materials are labile or not available. This position will teach and train new staff while providing daily support for the lab staff. Organizational skills and the ability to prioritize test requests are critical to successful performance. Multiple test requests, with different or the same priority, must be effectively organized by the individual in order to maximize diagnostic impact. A high degree of accuracy and reliability is required to ensure results. Schedule & Hours: Monday through Friday 8 AM to 5PM with flexibility including some 9 AM to 6 PM shifts and weekends at times. (Schedule is dependent on study activity/needs) Responsibilities: • Performs moderate and/or high complexity testing in the clinical laboratory., • Coordinates workflow/workload with colleagues as necessary to ensure timely reporting of results., • Skills to operate, calibrate, maintain, and troubleshoot analyzers and other lab equipment., • Ability to demonstrate competence in all laboratory procedures sufficient to perform at a satisfactory level without supervision., • Ability to use good judgement and decision-making sufficient to ensure accuracy and quality of lab tests., • Performs preventative maintenance on laboratory equipment and/or instruments. Suggests changes to maintenance schedules to meet the needs of the laboratory., • Performs troubleshooting as needed. Uses problem-solving skills when assessing test result accuracy and reliability to identify causes for unexpected test results., • Serves as a resource and mentor to less experienced lab staff and supports all training activities., • Ability to work as a team member by demonstrating behaviors that promote good co-worker relations. This includes professional appearance and interactions, positive attitude, and good relations with other clinical and site staff, physicians, vendors, and in supporting sponsor/client visits., • Verbal and written communications skills to listen attentively to staff and clients’ needs sufficient to answer questions, explain procedures, and give instructions., • Reviews select policies as required (i.e. annual review). Recommends policy changes and assists with communication of policy changes to testing staff. May also require communication about policy to other site staff., • Performs proficiency testing (PT) as required and assists with survey readiness/completion activities., • Assists in gathering data for validations, and with guidance, assists in data analysis., • Assists with organizing data for research activities and communication of such with other testing staff. Qualifications: • MLS (Medical Laboratory Scientist) ASCP (American Society for Clinical Pathology) Certification required, • Over 1 year of Clinical Research laboratory experience preferred, • High school diploma or equivalent required, • Bachelor's degree highly preferred Outstanding Benefits: • Retirement Savings Plan, • Paid Vacation, • Paid Holidays, • Paid Sick Time, • Employee Assistance Program, • Life Insurance, • Health, Dental, Vision (Generous employer contribution), • Long Term Disability Insurance EEO Minorities/Females/Protected Veterans/Disabled QPS is an equal opportunity employer. In accordance with anti-discrimination law, it is the purpose of this policy to effectuate these principles and mandates. QPS prohibits discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law. QPS conforms to the spirit as well as to the letter of all applicable laws and regulations.

Principal Data Scientist, Quantitative Intelligence (Consumer Transaction Data) Reports to: Head of Data Science About the role Our client, a leader in consumer purchase data and analytics, turns large-scale card transaction data into intelligence for brands, investors and agencies. 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. This is an individual-contributor tech lead role. You’ll guide the work of several data scientists, with a path to people management. A partner team handles data cleaning, merchant resolution and categorization. This role picks up from there: making the data statistically sound and predictive, then shipping it. What you’ll do • Own models end to end: design the methodology, build it, deploy it to production and monitor it., • Build the statistical layer that makes analysis on the data trustworthy: panel weighting, balancing, normalization, cohorting and bias correction., • Build predictive models from past behavior, such as spend prediction, category and brand trend forecasting, propensity and churn, and behavioral embeddings., • Apply causal methods (incrementality, synthetic control, uplift) where the problem calls for them., • Set technical direction, review the team’s work, and explain and defend methodology to stakeholders and clients. Must-haves • Hands-on experience with credit card or card transaction data., • A track record of shipping ML and statistical models to production yourself, not just analysis or prototypes. Strong production engineering in Python and SQL on a cloud data warehouse., • A deep statistics foundation: sampling, weighting and calibration, bias correction, and judging when a result can be trusted., • Predictive modeling and forecasting built on raw, transaction-level behavioral data., • [8+] years of experience, including leading the technical work of other data scientists., • Clear, concise communication of methodology. Nice to have • Causal inference and experimentation, as a complement to ML., • Representation learning and embeddings., • Privacy-preserving ML and data clean rooms. This role is not focused on fraud, AML, credit risk or loss/reserve forecasting, and it is not a pure experimentation or A/B testing role. Keywords: 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, Cleanrooms, Production ML Pipelines

MMRF OVERVIEW: The Multiple Myeloma Research Foundation (MMRF) is the largest nonprofit in the world solely focused on accelerating a cure for each and every multiple myeloma patient. We drive the development and delivery of next-generation therapies, leverage data to identify optimal and more personalized treatment approaches, and empower myeloma patients and the broader community with information and resources to extend their lives. Central to our mission is our commitment to advancing health equity so that all myeloma patients can benefit from the scientific and clinical advances we pursue. Since our inception, the MMRF has committed over $600 million for research, opened nearly 100 clinical trials, and helped bring 15+ FDA-approved therapies to market, which have tripled the life expectancy of myeloma patients. To learn more, visit www.themmrf.org. MMRF Core Values: At the MMRF our core values define both who we are and how we work together as an organization. We believe in investing in our team and building a culture that will help us pursue our highest level mission to accelerate a cure for each and every multiple myeloma patient. Our five core values are expressed below: • Prioritize Patients - Patients are at the center of everything we do. Every decision we make is grounded in the needs and best interests of the patients we serve., • Drive Innovation - We are committed to pursuing big, bold ideas. Taking risks, trying new approaches, and challenging the status quo are necessary to speed new discoveries., • Deliver Solutions - Taking on complicated challenges is what sets us apart. To deliver results, we must be decisive, take action, and act with urgency on behalf of the myeloma community., • Do It Together - We know that together, we are stronger. We work cross-functionally with the entire community to achieve our mission and are invested in the success of others., • Build Trust - We build trust-based relationships. We advocate for each and every myeloma patient by committing to diversity, equity, and inclusion and treating others with respect. Position Overview: The MMRF is seeking an experienced computational biologist to serve as Scientist / Lead, Translational Data Platforms for the MMRF Virtual Lab, our cloud-native translational research platform accelerating discoveries for the global multiple myeloma research community. This is a unique opportunity for a computational scientist who is passionate about translating complex biological questions into scalable technology solutions that empower researchers around the world. The successful candidate will combine expertise in computational biology, cancer genomics, and scientific analysis with product leadership, stakeholder engagement, and program management to drive the continued evolution of one of the world's leading myeloma-focused multi-omic research platforms. Working closely with the Director of Translational Research, you will assume day-to-day ownership of the Virtual Lab product roadmap, helping define the future direction of a next-generation computational research platform at the intersection of translational science, cloud technologies, artificial intelligence, and product innovation. You will work collaboratively with computational biologists, software engineers, clinicians, cloud architects, academic collaborators, technology partners, and scientific leadership to translate research priorities into innovative platform capabilities that accelerate biomedical discovery. This role is specifically designed for a computational scientist who wishes to remain actively engaged in scientific research while leading the development and evolution of research software products. You will continue contributing to computational analyses, development of bioinformatics workflows, translational research, scientific publications, and conference presentations, ensuring that scientific discovery remains central to your role while serving as the scientific owner of the platform. 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 generation of discoveries in multiple myeloma. This position is ideal for an experienced computational biologist who is ready to expand into scientific product leadership without stepping away from the science, offering the opportunity to contribute to the continued evolution and development of the platform with global impact while remaining at the forefront of translational cancer research. Primary Responsibilities: Scientific Product Leadership: • Serve as the scientific product owner for the MMRF Virtual Lab and primary scientific liaison for platform users and collaborators., • Define, maintain, and execute the platform product roadmap in partnership with scientific leadership., • Translate scientific priorities into clear technical requirements and product specifications., • Prioritize new capabilities based on researcher needs, organizational objectives, and strategic opportunities., • Coordinate feature planning, testing, release management, and continuous platform improvement., • Ensure platform development consistently delivers meaningful scientific value while maintaining an exceptional user experience., • Drive long-term evolution of the platform through continuous engagement with internal and external stakeholders. Computational Biology & Scientific Innovation: • Perform computational biology and bioinformatics analyses supporting translational research initiatives., • Develop, prototype, and validate analytical workflows for future incorporation into the MMRF Virtual Lab., • Collaborate with multidisciplinary teams to translate biological questions into scalable computational solutions and platform capabilities., • Evaluate emerging computational methodologies and AI-enabled technologies for integration into future platform capabilities., • Actively participate in collaborative analyses of patient data including clinical variable, tumor cell gene expression and DNA abnormalities as well as single-cell and spatial RNA sequencing data., • Contribute to peer-reviewed publications, conference abstracts and presentations., • Support biological interpretation of complex multi-omic datasets. Scientific Leadership & External Engagement: • Support biological interpretation of complex multi-omic datasets., • Coordinate cross-functional platform development activities across scientific, engineering, and external partner teams., • Represent the MMRF and the Virtual Lab at scientific meetings, workshops, and collaborative initiatives., • Manage relationships with external software development partners, cloud providers, academic collaborators, and technology vendors to support successful platform delivery., • Develop scientific documentation, demonstrations, and educational materials supporting platform adoption and user engagement. Qualifications & Experience: Required Qualifications: • PhD in Computational Biology, Bioinformatics, Cancer Genomics, Computer Science, Biomedical Informatics, or a related quantitative discipline., • Demonstrated experience applying computational approaches to biological or clinical research., • Expertise analyzing large-scale genomic cancer datasets including tumor gene expression and DNA abnormalities and scRNAseq of tumor and the immune microenvironment., • Strong scientific publication record demonstrating contributions to computational biology, bioinformatics, genomics, or related fields., • Experience developing computational analyses, bioinformatics workflows, analytical software, or research tools., • Experience leading or coordinating multidisciplinary scientific or technical initiatives involving multiple stakeholders., • Strong understanding of modern software development practices and the ability to work effectively with software engineering teams., • Excellent written, verbal, and interpersonal communication skills, with the ability to communicate effectively across scientific, technical, and executive audiences., • Strong organizational and project management skills, with the ability to manage multiple complex initiatives simultaneously. Desired Qualifications: • Experience serving as a scientific product owner, scientific product lead, technical lead, or similar role supporting the development of research software or computational platforms., • Experience managing external software development partners, technology vendors, or multi-institution scientific collaborations., • Background in cancer genomics, precision oncology, translational research, or biomedical data science., • Experience working with cloud-based computational research environments, particularly AWS., • Familiarity with biomedical data commons, FAIR data principles, or platforms such as Gen3., • Experience developing scalable bioinformatics workflows, computational pipelines, or analytical platforms., • A passion for building innovative technologies that accelerate biomedical discovery and improve outcomes for patients. EEO Statement: The Multiple Myeloma Research Foundation (MMRF) is an equal opportunity employer and does not discriminate against any candidate based on race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, military and veteran status, sexual orientation, or any other factor protected by federal, state, or local law. The MMRF does not sponsor/facilitate any type of work authorization for this role. All applicants must currently have original valid unrestricted authorization to accept new employment in any role in the U.S. with any employer. There is also no future employer-provided sponsorship for this role to obtain or extend authorization to work in the U.S.

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.

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.

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

This is not a conventional data science management role. Bachelor of Science or Bachelor of Arts from an accredited institution. 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 t

People Analytics & Research is a strong team of Data Scientists, Data Engineers, and Analysts. The People Analytics & Research team is looking for an experienced Data Scientist to lead and/or contribute to our most important research - applying causal inference and quasi-experimental methods to high

Skool is hiring its first ever Data Scientist. You’ll join our Data team, report to our Head of Data, and help shape how data science is used across the company. This is a hands-on role for someone who wants to grow a consumer product by building new ways for users to discover the right communities and people, including feed, search, recommendations, and matchmaking, and by testing what drives engagement and growth. One of our biggest areas of focus is helping users find the right communities and people on Skool. You’ll help us build and improve that experience through recommendations, ranking, and personalization, while also partnering closely with Product, Growth, and Engineering on engagement, activation, retention, and advertising. We’re looking for someone who can dig into ambiguous problems, find the real opportunity, and turn analysis into action. This is a 100% remote position. Skool has an office in Los Angeles, but we work as a distributed team. What you’ll do • Build models and algorithms for feed, recommendation, ranking, and search to help users discover relevant communities and people, • Own data science work across growth, product, and user engagement, from analysis through measured results, • Use real-time data to find opportunities, test ideas quickly, and refine models based on outcomes, • Develop predictive models for activation, retention, and other key funnels, • Design and run experiments, analyze results, and turn findings into clear product and business decisions, • Partner with Growth to test and improve advertising, including measuring its impact on acquisition and engagement What we’re looking for • You have deep data science experience and a track record of using analysis, experiments, and models to grow a consumer product, • You have hands-on experience building recommendation, matchmaking, ranking, search, or personalization systems, • You have a strong foundation in machine learning and statistical modeling using tools such as Python and scikit-learn, • You favor quick action and experimentation over long analysis and can build enough conviction in your work to bet on it, • You are comfortable managing real budget, being wrong, learning quickly, and making the next bet, • You can own ambiguous problems, decide what matters, and move without waiting for permission, • You are strong at data analysis and tool-agnostic. You care about accurate results and business impact more than a specific stack, • You can write enough production-quality code to implement or partner closely on real-time solutions when offline analysis isn’t enough, • Bonus: You have hands-on experience optimizing advertising, acquisition, or other performance marketing systems Why join Skool? • Over 30M users, 150K communities, $1B in creator revenue + already profitable (!), • Fast-growing, mission-driven company with a focus on education and community, • We’re a small, collaborative team that likes to have fun while prioritizing balance, • Remote-first, industry-leading compensation, fully covered medical, dental, and vision insurance (including dependents), 401(k) matching, and more!

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.

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. * This begins as a 1 year contract with an opportunity to extend or convert at any time * Position Summary We are seeking a Data Scientist to develop and evaluate AI solutions for legal content workflows. The role focuses on large language models, natural language processing, and reliable data pipelines. Experience with traditional machine learning is a strong plus. The successful candidate will collaborate with engineers, product stakeholders, and legal subject matter experts to translate business requirements and editorial feedback into measurable improvements. This role requires strong Python skills, sound experimental judgment, and the ability to independently investigate issues and deliver working solutions. Key Responsibilities • Develop and improve LLM-based workflows for information extraction, classification, legal summarization, and content generation., • Design and evaluate prompts, retrieval-augmented generation (RAG), and multi-step agent workflows., • Build reliable data-preparation pipelines, including parsing, transformation, validation, caching, and recovery from interrupted processing., • Create representative evaluation datasets and conduct controlled experiments, error analysis, and regression testing., • Work with subject matter experts to assess factual accuracy, completeness, source support, and consistency, and translate feedback into generalizable improvements., • Diagnose problems across data, retrieval, model behavior, and application logic., • Balance output quality, latency, and cost when comparing technical approaches., • Maintain tested, version-controlled code and clear documentation to support reproducibility and team handoffs. Required Qualifications • Bachelor’s degree or higher in computer science, Data Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience., • At least 3 years of relevant experience in data science, machine learning, or NLP, including hands-on experience developing LLM-based applications., • Strong Python programming skills and experience with SQL and structured or semi-structured data, such as JSON and XML., • Practical experience with prompt design, structured outputs, retrieval, and systematic LLM evaluation., • Understanding of statistical evaluation, train/validation/test separation, data leakage, and appropriate performance metrics., • Experience using Git, debugging existing code, and writing automated tests., • Ability to communicate findings clearly, incorporate feedback, and proactively raise delivery risks. Preferred Qualifications • Experience with traditional machine learning, including feature engineering, classification, tree-based models, and imbalanced datasets., • Familiarity with scikit-learn, PyTorch, or comparable frameworks., • Experience fine-tuning transformer models for classification, information extraction, or sequence labeling., • Familiarity with AWS, particularly S3 and EC2, and Linux or GPU-based training environments., • Experience with legal documents, editorial workflows, or other accuracy-sensitive domains.

Senior Bioinformatics Scientist ( ctDNA ), San Diego, CA / Remote (US) - $150,000 - $180,000 Are you passionate about advancing cancer diagnostics through cutting-edge bioinformatics and testing? Our client, an innovative biotechnology company focused on molecular diagnostics, is seeking a Senior Bioinformatics Scientist to lead the development of next-generation laboratory-developed tests in a highly collaborative and regulated environment. Who you are: • PhD in Bioinformatics, Computational Biology, Genomics, Biostatistics, or a related quantitative field (or MS plus additional industry experience)., • 6+ years of experience in biotech, diagnostics, or regulated healthcare environments., • Hands-on experience developing NGS-based clinical assays, including ctDNA and MRD applications are a must., • Strong Python programming skills with experience building production-grade bioinformatics pipelines and following SDLC best practices., • Proven success working within CAP/CLIA, IVD, FDA, or similarly regulated development environments. What you'll do: • Lead bioinformatics strategy, development, optimization, and validation efforts for MRD diagnostic assays., • Design and execute analytical studies evaluating assay performance, including sensitivity, accuracy, reproducibility, and limit of detection., • Develop and maintain scalable bioinformatics pipelines for QC, variant calling, MRD detection, and reporting., • Collaborate with assay development, clinical, quality, regulatory, software, and data science teams to deliver validated solutions., • Mentor junior scientists and contribute to technical documentation, audits, and regulatory submissions. What does this position pay? Compensation is determined by several factors which may include skillset, experience level, and education. The expected range for this role is $150,000-$180,000 per year. Please note this range is an estimate and actual pay may vary based on qualifications and experience. What's next? Please email your resume to if you're excited to explore this opportunity with our client. We actively support and promote people of various backgrounds, from race, religion, gender to geographical area, university, lifestyle, and personality type. Proven Recruiting is minority-owned, majority women, and is a strong advocate for diversity and inclusion in the broader community. Apply today!

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

We are seeking a Data Scientist, Associate to build RoboStrategy’s data capability from the ground up. Join the team at RoboStrategy as Data Scientist, Associate. Bring together shareholder records, 13F filings, DTC position reports and allocator databases into a single view connected to our CRM,

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

Data Scientist (Live Anywhere). Perform Exploratory Data Analysis (EDA). Proven track record of deploying models and data pipelines in cloud environments, preferably on GCP or other cloud platforms.

Perform deep EDA, data profiling, and quality audits to ensure model-ready data standards. Proven ability to own and deliver end-to-end data science projects independently. Snowflake Data Cloud: querying, Snowpark for Python ML pipelines.

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

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

Leverage Verasight’s data pipelines and processing procedures to own the data collection and quality process from end to end, including: building contact lists and sampling frames, monitoring survey fielding, cleaning and analyzing survey response data, writing methodology documentation, and prepa

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.This is a hands-on senior role.You will own problems end to end — scoping

Description Remote Our client seeks a Principal Data Scientist to scale Data Science and AI capabilities for end-to-end payment optimization. The role will collaborate with ML engineers and product partners to design and deploy real-time models and intelligent decision engines, drive strategy and roadmaps, lead cross-functional initiatives, and mentor senior data science talent. The position balances strategic leadership with hands-on contribution across architecture, design reviews, code reviews, and select implementation to deliver production-grade ML solutions. This is a contract to hire opportunity. Applicants must be willing and able to work on a w2 basis and convert to FTE following contract duration. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $85.00 to $95.00/hr. w2 Responsibilities • Define technical vision and strategy for data-driven product initiatives focused on payment optimization, aligned to business goals., • Develop scalable and reusable capabilities for real-time ML models including classification, ranking, optimization, rapid experimentation, and continuous monitoring., • Oversee and contribute to conceptualization, development, deployment, operation, validation, and maintenance of ML models and update systems., • Establish and enforce best practices for ML modeling while evaluating and adopting modern tools, frameworks, and infrastructure., • Foster a culture of innovation, experimentation, and collaboration while mentoring an elite team of data scientists., • Partner with product, engineering, data, and compliance teams to integrate ML into products and communicate complex concepts to varied audiences., • Collaborate with Data Science leaders to establish an operating model for ML R&D that optimizes end-to-end delivery of business value. Experience Requirements • Bachelor’s or master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field. PhD preferred., • 7+ years in ML research or engineering with 5+ years building large-scale, real-time ML systems in production, including hands-on experience., • Expertise in machine learning, statistical modeling, and data analysis with strong experience across the ML lifecycle and experimentation., • Proficiency in Python (Pandas, NumPy, scikit-learn) and strong SQL experience. NoSQL or graph databases are a plus., • Demonstrated ability to lead solution design and execution, translating complex business requirements into actionable technology solutions., • Exceptional communication skills with the ability to influence and collaborate across technical and business audiences, including executives., • Bonus: Experience in payments, fintech, or financial services. Knowledge of payment systems such as authorization lifecycle, tokenization, fraud and risk, and real-time payments. Experience with cloud platforms including AWS, GCP, Snowflake, Databricks, or Vertex AI. Agile development experience. Background in large companies, mature ML teams, or regulated industries. Education Requirements • Bachelor’s or master’s degree in a relevant field. PhD preferred.

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. This role is ideal for someone who enjoys working with data, automation, and emerging AI tools in a collaborative, fast

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

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

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.

Type: Temp (6–9 months) • Location: Remote US TZs Target Roles: Forward Deployed Engineer, Senior ML Engineer, Research Engineer/Scientist (Alignment), AI Product Manager Own the top of funnel: map the market, generate calibrated pipelines fast, and hand off HM-ready prospects with crisp notes. No “post & pray.” What You’ll Do (Sourcing-First) • Market mapping: Build company/lab/OSS target lists; track movers (arXiv, OpenReview, Google Scholar, Hugging Face, GitHub)., • Outbound at scale: Tailored outreaches; iterate subject/copy; test 3–5 variants; maintain reply metrics., • Profile calibration: Validate signals (repos, papers, shipped features, MLOps stack, product outcomes)., • Light pre-screen (10–15 min): Confirm level, comp ballpark, work auth, location, timeline, and role fit; capture structured notes., • Handoff: Package candidates with scorecard snapshot + links; book with recruiter/HM. Role Signals You’ll Target • FDE: Customer-facing build/ship, Python + data wrangling, rapid proto, consultative comms., • Senior ML Eng: Prod LLM/ML (inference, RAG, fine-tune, evals), MLOps (deploy/observability)., • Research/Alignment: Strong math/ML fundamentals; safety/evals/interpretability/RLHF artifacts., • AI PM: Shipped AI features, experiment cadence, metric/latency/trade-off literacy. Must-Haves • 2+ years sourcing for deep eng/ML/AI roles, • Tools: ATS, LinkedIn Recruiter, GitHub search, arXiv/Scholar, Notion/Airtable, Gem/Fetcher., • Clean pipeline habits Engagement • 30–40 hrs/week

Data Analyst / Data Scientist (Utility Analytics). Analyze large utility datasets—including AMI usage, Customer Care & Billing (CC&B), and customer engagement data—to identify trends, patterns, anomalies, and quality issues. Direct experience working with Advanced Metering Infrastructure (AMI) a

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. Design and implement robust statistical models and machine l

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,

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

Senior Interior Designer/Project manager .As a member of our design team, you’ll play a key role in shaping residential interiors that reflect each client’s vision and lifestyle.From developing inspired design concepts to refining the details that bring a project together, you’ll be involve

This role combines maritime-domain awareness with hands-on geographic information systems, data integration, and data-engineering capabilities. Our core areas of expertise are in the fields of Digital Transformation, Cloud Solutions, SaaS and Low-Code/No-Code Solutions, Emerging Technologies, Data A

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. Build and apply codebooks using both deductive and inductive ap

Partner with technical and integration teams to ensure event data, imports, integrations, testing, and platform configuration are completed accurately and on schedule. Comfortable working with event data, registration platform configuration, native integrations, imports, testing, and technical tea

When you request access to your personal data, some information may be redacted if it includes the personal data of other individuals or information that we must protect in order to preserve their privacy rights. We protect any such data transfer between Keeper entities using appropriate safeguards

Manage input and delivery of work products from internal team members to ensure that new data center spaces comply with the project requirements, customer requirements, all engineering standards, applicable codes, and specifications. Datacenter experience is preferred. As Project Manager you will be

As a Technical Project Manager, you will play a key role in the successful implementation of international customer onboarding and rollouts.You will support our customers from project planning and installation to successful go-live and handover into operation.You combine technical implementation exp

Bring your monitoring expertise to the forefront of innovation.Clinical Research Associate (CRA).Allucent, you will independently control and monitor investigational sites, pro-actively detect issues, provide solutions to ensure clinical studies are performed according to the trial protocol and in c

Climate Finance Solutions (CFS) is a global consultancy that helps companies and organizations secure large-scale grant funding for climate solutions.To date, our team has secured over $1.Europe, the US, Canada, Australia, and emerging markets worldwide.As a mission-driven company, we are committed

The BIDA-II may also be tasked with conducting Internet searches to identify best practices or common policies related to Business Intelligence (BI), data governance, AWS data pipelines, and mentoring analysts in other departments in how to build and modify Power BI datasets and reports. BA/BS with

Familiarity with APIs, system integrations, data mapping, databases, or other technical concepts relevant to Encompass. Independently discover opportunities to reduce manual work, improve data quality, and increase efficiency in our Encompass workflows, and incorporate these ideas into our project p

Absci offers AI Scientists a unique opportunity to both develop novel, cutting edge machine learning models and apply these models directly to identify novel targets, unlocking previously intractable disease interventions, and to generate candidate antibody therapeutics. Maintain our own Wet Lab, en

Proficient knowledge and skills to support program specific data review, trend identification, data interpretation. This includes activities relating to study design, data generation and validation and data analysis and interpretation. Provides medical monitoring support or oversight of activities c

Partner with product, design and data as a peer, shaping what's worth building from the start. The thing that sets you apart: you build custom representations from raw data instead of reaching for the off-the-shelf embedding. AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.

This is an exciting opportunity to join a growing data center development organization and play a critical role in delivering the electrical infrastructure necessary to bring significant new data center capacity online. Monitor construction schedules and proactively address potential delays impactin