Data Scientist Algorithms Community Support Jobs

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart’s Marketing Data Science and Analytics team partners across Marketing, Strategic Finance, and Product to power data-driven growth. As a Senior Marketing Decision Scientist II, you will shape how we measure, forecast, and optimize marketing performance across channels, helping Instacart make smarter investment decisions and accelerate customer acquisition and retention. This is a high-impact, high-visibility role on a small, focused team where you will own complex, zero-to-one measurement initiatives and scale proven solutions. You will collaborate closely with channel marketers, growth leaders, finance partners, and data engineers to deliver models and experimentation frameworks that inform multi-million-dollar decisions. If you thrive in a fast-paced environment that still moves like a startup—and you love rolling up your sleeves to turn ambiguo

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

Job Title: Lead - Aggregate Reporting Employment Type: Full-time Work Type: Remote About ClinChoice: ClinChoice is a partner to the largest pharmaceutical, medical device, and consumer care innovators in the world. Established in 1995, we provide expertise in clinical operations, biometrics, regulatory affairs, pharmacovigilance, medical affairs, and toxicology to help our partners advance healthcare by accelerating clinical trials with data-driven insights, delivering the best strategies for product registration, and enhancing patient safety through real-world and clinical analysis. Our global delivery network has expanded to centers and satellite offices in the United States, Mexico, the United Kingdom, Armenia, China, Japan, India, and the Philippines to help our customers maintain regulatory compliance locally and globally. We have forged future-defining partnerships with industry bodies and technology companies to develop cutting-edge solutions that deliver our expertise with quality and precision. Primary Responsibilities: Responsible for authoring Aggregate Safety Reports (including but not limited to PBRER/PSUR, ACO, DSUR, PADER, CAR, RMP, Ad-hoc safety reports for medicinal and non-medicinal products and EU-MDR PSUR, PMSR, PMSP, and PRER reports for medical devices, and Cosmetovigilance reports for Cosmetic products for submissions to various health authorities as per the requirement). Plan report-specific timelines, identify relevant stakeholders, request calls for contributions, and coordinate with various stakeholders for obtaining relevant data for the preparation of aggregate safety reports. Review the safety data (including the seriousness and expectedness assessments of events, as may be necessary) as per the agreed strategy and sponsor’s conventions and verify the correctness and completeness of contributions received from stakeholders. Perform aggregate review of post-marketing cases received in global databases and assess whether the cases alter t

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

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

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Position Overview We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. This role can be based out of our Palo Alto office, or remotely in the United States. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues Strong background in machine learning, deep learning, and natural language processing Experience building complex neural networks for language and visual understanding Capable of conducting rigorous empirical studies to validate theoretical results Excellent leadership, problem-solving, and communication ski

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. Position Overview We are seeking a Senior Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field Strong background in machine learning, deep learning, and natural language processing Familiarity with training distributed training of neural networks for language and visual understanding What We Offer Opportunity to work on real-world problems at the cutting edge of AI research Opportunity to utilize research vision to innovate the entire company and make real-world impact Exposure to the full lifecycle of AI model development, from research to production Our compensation (base + equity) for this position is competitive with frontier AI labs About MongoDB

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe that achieving our goal requires real world deployment and iteratively updating based on what we learn. The Protection Scientist Engineer, Integrity team supports this by identifying and investigating misuses of our products – especially new types of abuse. This enables our partner teams to develop data-backed product policies and build scaled safety mitigations. Precisely understanding abuse allows us to safely enable users to build useful things with our products. About the Role Protection Science Engineering is an interdisciplinary role mixing data science, machine learning, investigation, and policy/protocol development. As a Protection Scientist Engineer within Integrity and Investigations, you will be responsible for designing and building systems to proactively identify and enforce on abuse on OpenAI’s products. This includes ensuring we have robust abuse monitoring in place for new products, sustaining monitoring for existing products, and prototyping and incubating systems of defense against our highest risk harms. You will also respond to and investigate critical escalations, especially those that are not caught by our existing safety systems. This will require expert understanding of our products and data, and involves working cross-functionally with product, policy, and engineering teams. This role is based in our London office and includes participation in an on-call rotation that will involve resolving urgent escalations outside of normal work hours. Some investigations may involve sensitive content, including sexual, violent, or otherwise-disturbing material. In this role, you will: Scope and implement abuse monitoring requirements for new product launches. Improve processes to sustain monitoring operations for existing products, including developing approaches to automate monitoring subtasks. Prototype and mature into product

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe that achieving our goal requires real world deployment and iteratively updating based on what we learn. The Protection Scientist Engineer, Integrity team supports this by identifying and investigating misuses of our products – especially new types of abuse. This enables our partner teams to develop data-backed product policies and build scaled safety mitigations. Precisely understanding abuse allows us to safely enable users to build useful things with our products. About the Role Protection Science Engineering is an interdisciplinary role mixing data science, machine learning, investigation, and policy/protocol development. As a Protection Scientist Engineer within Integrity and Investigations, you will be responsible for designing and building systems to proactively identify and enforce on abuse on OpenAI’s products. This includes ensuring we have robust abuse monitoring in place for new products, sustaining monitoring for existing products, and prototyping and incubating systems of defense against our highest risk harms. You will also respond to and investigate critical escalations, especially those that are not caught by our existing safety systems. This will require expert understanding of our products and data, and involves working cross-functionally with product, policy, and engineering teams. This role can be based in either our San Francisco, or NY office and includes participation in an on-call rotation that will involve resolving urgent escalations outside of normal work hours. Some investigations may involve sensitive content, including sexual, violent, or otherwise-disturbing material. In this role, you will: Scope and implement abuse monitoring requirements for new product launches. Improve processes to sustain monitoring operations for existing products, including developing approaches to automate monitoring subtasks. Prototyp

What You Will Achieve A Senior Associate Scientist (R2) position is available in the Conjugation Process Development group of Bioprocess R&D in USA - WA - Bothell. We’re seeking a passionate and creative individual to join a dynamic team of scientists and engineers focused on developing robust, scalable, and high productivity conjugation processes for the manufacture of antibody-drug conjugates (ADCs) for early- and late-phase clinical programs. The work will also involve working with commercial and clinical production facilities to ensure accurate technology transfer and successful large-scale production. You may also be involved in cutting-edge technology development projects that seek to discover new innovations for ADC process development and/or manufacturing. How You Will Achieve It Design, plan, and execute milligram to gram-scale conjugation experiments in the development laboratory. Ensures timely, effective, and high-quality documentation in electronic laboratory notebooks and internal technical reports. Communicate results and findings to stakeholders on a regular basis; present data/strategy to colleagues and management in internal and external venues (technical meetings, project team meetings, and conferences, etc.) as appropriate. Assist in or lead the technology transfer of manufacturing processes to clinical and commercial manufacturing facilities. Provide support and troubleshoot during manufacturing campaigns as needed. Work collaboratively with colleagues both within the group and cross-functionally; contribute to maintaining and improving upon our safe, effective and efficient lab operations. Qualifications Must-Have BS/BA in Chemistry, Biochemistry, Chemical/Biochemical Engineering, or other related disciplines with 3-4 years of experience, or MS in the above fields with 0-2 years of experience.