Data Scientist in United States

About the Team The Youth Well-Being product team is part of the Integrity pillar at OpenAI, responsible for ensuring that our state-of-the-art AI technologies are deployed in safe, age-appropriate, and beneficial ways—especially for youth and families. We work across OpenAI’s entire product surface area, from ChatGPT to future-facing tools, to architect safety and trust into the foundation of our systems. Our mission: empower families while meeting the highest standards of regulatory compliance and ethical responsibility. This work is core to OpenAI’s mission to ensure AGI benefits all of humanity. Safety, especially for the most vulnerable users, is more important to us than unfettered growth. About the Role We’re looking for a Senior Software Engineer to help architect and build the foundational systems that power family- and youth-facing experiences at scale. You’ll help define how teens and guardians engage with OpenAI products—ensuring those experiences are safe, compliant, and empowering. You’ll operate across a broad technical surface: building identity primitives, age assurance pipelines, and guardian tools that support both proactive and reactive interventions. You’ll collaborate closely with a cross-functional team of engineers, data scientists, designers, user researchers, and policy experts. This is a high-impact, 0→1 opportunity to set the standard for how families interact with generative AI. In this role, you will: Architect and implement teen and guardian experiences across OpenAI products, including ChatGPT. Build global age assurance systems that are privacy-preserving and tailored to regional compliance needs. Design and evolve our identity infrastructure to support scalable, secure, and resilient user journeys at consumer internet scale. Help define safety and well-being metrics, and continuously improve user trust through technical interventions. You might thrive in this role if you: Have built products or infrastructure for users under 18, or h

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building an AI powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for Software Engineers who're passionate about blending production-ready platform architecture with new tech and new paradigms. You’ll push the boundaries of OpenAI’s newest technologies to enable interactions and automations that are not only functional, but delightful. We value proactive, customer-centric engineers who can get the foundational details right (data models, architecture, security) in service of enabling great products. In this role, you will: Own the end-to-end development lifecycle for new platform capabilities and integrations with other systems Collaborate closely with engineers, data scientists, information systems architects, and internal customers to understand th

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Working at Abbott At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to: · Career development with an international company where you can grow the career you dream of. · Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year. · An excellent retirement savings plan with a high employer contribution. · Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree. · A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune. · A company that is recognized as one of the best big companies to work for as well as the best place to work for diver

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We’re looking for a Senior Applied Scientist to help drive the future of credit applied science at Ramp. In this role, you will design, build, and optimize the models that power our credit risk systems, helping us make faster, smarter, and more scalable risk decisions for our customers. You’ll work at the intersection of machine learning, statistics, economics, and product strategy. This role requires strong technical depth as well as close collaboration with business, product, data, and engineering partners. You will help identify high-impact opportunities, translate ambiguous business problems into rigorous modeling work, and ship models that operate reliably in production. Applied scientists at Ramp focus on solving quantitative problems across credit, fraud, growth, and our core product by applying the right mix of machine learning, causal inference, structural modeling, and optimization. What You'll Do Design, build, and optimize machine learning models that support credit risk decisioning and portfolio management at Ramp Own the

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen of our business decisions and to empower and scale product innovations. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, economics, and machine learning. Aligned and partnering with product groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure the impact / incrementality on our community of players, developers, and advertisers. WHY ADVERTISING SCIENCE? Advertising at Roblox is new, facing critical scale, effectiveness, and implementation challenges, while operating in our civility and user focused experiences. As a new strategic area, work will be innovative and impactful. Scientific rigor will be critical in success as we organize our data model, design principled measurement systems, and architect the future of incrementality measurement and actioning, to enable our communities. In this role, you will contribute to the new A

Become a part of our caring community Humana’s Quality and Cost Strategy Analytics Team is seeking a Research Scientist 2 (Remote). Healthcare is rapidly changing, and our members are living longer, often with more chronic conditions. The Quality and Cost Strategy Analytics team identifies opportunities and build solutions to improve clinical outcomes and lower costs for millions of Medicare Advantage beneficiaries leveraging data science & analytics, clinical expertise, strategic mindset, and rigorous study designs. In this multi-disciplinary team, you will have the opportunity to work closely with strategy partners and clinicians to shape Humana’s future enterprise clinical strategies and initiatives. The Research Scientist 2 will lead research, evaluation and development of opportunities that optimize healthcare delivery, lower medical cost while improve member health outcomes, through applying mathematical, statistical, epidemiologic and data science methods. The Research Scientist 2 will also partner with stakeholders across the enterprise to identify, prioritize and measure the impact of core and novel solutions to significant problems in healthcare and improve the health of especially underserved population, using high volumes of structured and unstructured data. Responsibilities As a Research Scientist 2, you will: Research, prototype and scale new ideas to improve population health and healthcare delivery Collaborate with analytic and business teams to set objectives, approaches, and work plans Collaborate with strategy to evaluate existing programs and identify and measure new solutions to impact healthcare Leverage a wide range of analytics methods ranging from descriptive to prescriptive to transform high volumes of complex data into analytics solut

ROLE SUMMARY This is a laboratory-based position within the Vaccine Research and Development, EBPD – Analytical GLP laboratory group. The individual will perform routine sample testing, assay verification and qualification studies in support of material characterization for vaccine GLP toxicology studies. Assays include but are not limited to enzyme-linked immunosorbent assays (ELISAs) and other plate-based testing, Antigenicity by MSD and Hamilton, HPLC, spectroscopic techniques (UV-Vis), Endotoxin, Bioburden, pH and Appearance. This position will require work on fast-moving high-visibility projects within regulated GLP laboratory environment. ROLE RESPONSIBILITIES Under direct supervision, perform sample testing in support of toxicology studies, including release, stability, and assay qualification. Ability to perform necessary calculations independently and discuss conclusions with their manager. Document experiments and analyze data from sample testing and method qualification experiments using an electronic laboratory notebook and LIMS with guidance. Contribute to the authoring of technical documents including assay qualification reports, analytical test methods, stability protocols/reports. Assure safety and compliance. Provide daily laboratory operations support. QUALIFICATIONS Basic Qualifications: BS or BA degree in biology or related discipline with 0- 2 years relevant experience. · Basic knowledge of bioassay analytical techniques. Strong verbal and written communication skills. Proficiency with personal computers including word processing, spreadsheets, PowerPoint and relevant scientific software is required. Preferred Qualifications: Prior experience work

Use Your Power for Purpose At Pfizer, our purpose is to deliver breakthroughs that change patients’ lives. In this role, you will contribute to the discovery and advancement of innovative medicines for patients worldwide by applying rigorous science, modern pharmacology, and cutting-edge technologies. Your work will help transform promising therapeutic ideas into high-quality experimental data that enable confident decisions across the drug discovery process. What You Will Achieve A key strategic focus within the Internal Medicine Research Unit (IMRU) is the discovery of novel therapies for obesity, cardiovascular disease, and related cardiometabolic conditions. As an Associate Scientist in the In Vitro Pharmacology group, you will contribute to early drug discovery programs by generating rigorous, reproducible pharmacology data that support target validation, assay development, compound profiling, and mechanism-of-action studies. This role is well suited for a collaborative, hands-on scientist with experience in cell-based assay execution, mammalian cell culture, quantitative data analysis, and an interest in receptor pharmacology within cardiometabolic drug discovery. How You Will Achieve It Develop, optimize, and execute cell-based signaling, ligand-binding, and other in vitro pharmacology assays to generate high-quality data that support project decisions. Support compound profiling and mechanism-of-action studies through careful experimental design, troubleshooting, and quantitative data analysis. Maintain mammalian cell cultures and prepare fit-for-purpose cellular or membrane-based assay reagents to support screening, binding, and functional assay workflows. Apply core pharmacology concepts, including ligand potency, efficacy and affinity to interpret experimental results. Work collaboratively with pharmacology colleagues and cross-functional pr

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary At CVS/Aetna, we're pioneering a total approach to health and wellness. As a Decision Scientist on the Analytics & Behavior Change team, you'll build industry-leading analytics, data, and technology platforms to help reimagine health care. This position will play a critical role within a cross-functional team, delivering powerful solutions. Utilization Management (UM) ensures consistent delivery of the right care, in the right setting, by the right people. The UM Data Science team leverage data, analytics and AI solutions to transform UM operations and optimize provider and member experience. Develop analytic solutions to optimize Utilization Management in healthcare Explores, examines and interprets large volumes of data in various forms Performs analyses of structured and unstructured data to solve moderately complex business problems Utilizing advanced statistical techniques and mathematical analyses Develops data structures and pipelines to organize, collect and standardize data that helps generate insights and addresses reporting needs Uses data visualization techniques to effectively communicate analytical results and support business decisions Creates and evaluates the data needs of assigned projects and assures the integrity of the data </u

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to the Quality leadership within Manufacturing Operations, the Senior Reliability Scientist is responsible for leading reliability activities across complex, high-performance systems. Working closely with established reliability experts and cross-functional teams, this role uses experimental data and advanced modelling to inform design decisions, validate product reliability and optimise serviceability strategies, including spares provisioning. The Team The Quality team within Manufacturing Operations is responsible for ensuring product robustness, reliability and lifecycle performance across Graphcore’s hardware portfolio. The team includes experienced reliability specialists and works closely with technology research, chip, board, system design, platform and operations teams to translate reliability insights into actionable improvements across the product lifecycle. Responsibilities and Duties: · Define and refine reliability requirements across silicon, board and system levels, working in partnership with research and design teams · Apply ad

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection, error outliers and faulty deployment analysis. As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performa

About the Team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Marketing team helps deeply understand customer audiences and market dynamics, influence the development of the right products, build sustainable and customer-aligned monetization models, and drive awareness, adoption, and usage across OpenAI’s products and platform. We take a data-driven approach to understand markets, develop monetization strategies, and uncover customer needs that shape product strategy and messaging. We partner closely with Sales, Partnerships, Product, Engineering, Research, Comms, and Design to deliver a cohesive end-to-end customer experience and lead go-to-market efforts for new product launches across channels. About the Role We’re looking for a Marketing Scientist to join OpenAI’s Ads Marketing Science function. Reporting to Marketing Science leadership, you’ll be a senior individual contributor who combines rigorous measurement expertise with strong client judgment and hands-on execution. Your mission is to help OpenAI Ads prove and improve advertisers’ media performance. You’ll work with sales, partners, and clients supporting all forms of measurement including verification, attribution, incrementality, brand, marketing mix modeling (MMM), and scalable advertiser reporting, connecting sound methodology to decisions advertisers can act on. You will partner closely with Sales on key advertising accounts and with Product, Engineering, Data Science, Partnerships, Legal, and Privacy. Initial priorities include advancing incrementality measurement, helping onboard measurement partners to privacy-forward measurement workflows and integrations, and creating reusable programs, tools, agents, skills, and workflows that let sales and clients access high-quality Marketing Science support at scale. This role is based in either San Francisco or New York, and follows a hybrid schedule (Monday-Wednesday). In th

About the Team OpenAI’s People team hires, engages, and retains world-class talent to safely build and deploy AGI that benefits all of humanity. The People Analytics team helps leaders make better, evidence-based talent decisions. About the Role As a People Research Scientist, you will bring deep expertise in research design, measurement, experimentation, and applied data science to OpenAI’s most important People programs. You will design studies, evaluate people processes, and help leaders better empower employees, strengthen organizational systems, and deliver exceptional employee experiences. This is a high-ownership individual contributor role combining hands-on research, methodological leadership, and scalable people science capabilities. We’re looking for an experienced researcher who can turn ambiguous People questions into rigorous designs, validated insights, and actionable recommendations. This role is based in San Francisco, CA or Mountain View, CA, with occasional travel to our San Francisco office. What You’ll Do: Design rigorous research and evaluation strategies for recruiting, organizational health, manager effectiveness, employee experience, and talent outcomes. Apply advanced statistical modeling, machine learning, and research methods to inform program design, evaluate effectiveness, and quantify business impact. Partner with People Operations, data engineering, and people systems teams to define data requirements, improve data quality, establish documentation standards, and ensure research datasets are governed, reproducible, and privacy-preserving. Build scalable people science infrastructure, including self-service agentic tools, automated validation workflows, reusable research datasets and analytical pipelines. Develop research playbooks that establish rigorous standards for study design, measurement, validation, and documentation, enabling high-quality, repeatable, and scalable research across the organization. Communicate findings through c

The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces—a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action – providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas. We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number — it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success. The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user’s query can result in the agent making decisions against dozens of visualizations and data sources – both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the evaluation strategy for Dashboards, as well as sister teams within our organization. Define the metrics — offline and online, quality and cost, single-turn and multi-turn — that the team and the broader organization optimize against. Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, an

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali