Scientist in United States

About the Role We’re hiring a Data Scientist to support Real Estate & Workplace (REW), a fast-moving global team focused on creating workplaces that help OpenAI’s people do their best work while scaling the company’s real estate and workplace operations. Our work is grounded in understanding how people use space and services, collaborate across physical and digital environments, and experience the workplace. REW’s scope spans portfolio strategy, design and construction, space planning, sustainability, workplace experience, and global operations. You’ll work comfortably across this broad, sometimes messy data landscape and build trusted relationships across the domain. The work informs high-impact decisions with immediate, visible effects—from where teams work and how space and services are allocated to which investments move forward and how workplace experiences evolve. This is a high-ownership Data Science role spanning analytical strategy and hands-on execution. Working at the forefront of AI-native analytics, you’ll help define the future of workplace operations at OpenAI rather than follow an established playbook. You’ll shape REW’s Data Science roadmap, identify where forecasting, experimentation, and optimization can drive impact, and translate business priorities into an analytical plan. You’ll own the stakeholder-facing execution layer—including owning agent-built dashboards, recurring reporting, models, and decision tools—along with analytical requirements, validation, adoption, and measurable business impact. In this role, you’ll be partnered closely with Finance, People Analytics, IT, and REW leaders. You’ll own problems end to end—from framing and prioritization through analysis, recommendation, delivery, adoption, and iteration—so the work drives measurable business outcomes. What You’ll Do Own ambiguous, high-impact problems end to end—from framing and prioritization through delivery, adoption, and iteration. Define success metrics and build measur

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a Data Scientist on our Analytics and Data Insights team, you'll work on problems that don't have textbook answers yet; building the analytics that shape product and company strategy, designing the experiments that prove or kill our biggest bets, and helping enterprise customers understand what foundational AI actually means for their bottom line. You'll own analytical work end-to-end: from framing the right questions and building the models to shipping insights, tools, and results that product leaders, sales teams, and enterprise customers rely on. As a Data Scientist, you will: Drive the mission forward. Build bleeding-edge agentic analytics: Agentic analytics is far from a solved problem, and we want to be the company that solves it. We need the sharpest minds with the curiosity, drive, and focus required to build the tools necessary to bring order and clarity to real world data. Define AI impact measurement: own the end-to-end analytics st

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 someone to help lead the future of analytics at Ramp. This person will enable Ramp to get 1% better every day by developing data products and insights. They will partner closely with business stakeholders and product, engineering, and design counterparts to prioritize and execute on work, improve reporting, as well as drive results and process improvements. What You’ll Do Full stack development, building models to consume, transform, and expose data to stakeholders and production systems Drive a culture of experimental design, testing agenda, and best practices Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way Collaborate with P/E/D/D (product, engineering, data and design) teams to develop product roadmaps and measure success Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action Wha

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. What You’ll Do Full stack development, building models to consume, transform, and expose data to stakeholders and production systems Drive a culture of experimental design, testing agenda, and best practices Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way Collaborate with Finance teams (e.g. GTM Finance, StratFin) to develop financial insights and influence business decisions Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action What You Need Minimum of 3 years of industry experience in Data Science / Software Engineering / Finance Strong AI proficiency as a lever to quickly adopt new skills and subject matter Track record of shipping high quality products and features at scale Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical so

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role: We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. To realize this vision, we need people who are obsessed with understanding how users experience our product and can turn that understanding into decisions that move the needle. You'll directly impact Replit's growth by turning user behavior into actionable insights that shape product strategy, improve activation and retention, and drive sustainable revenue growth across our self-serve and enterprise segments. Who You are You're a data scientist who moves fast and goes deep. You can spin up an analysis in hours that would take others days; not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You're the person who digs past the top-line number to find the confound, questions whether the metric actually measures what people think it does, and pressure-tests your own work before anyone else sees it. You treat experimentation as a craft, not a checkbox. You've felt the pain of underpowered tests and novelty effects, and you have the judgment to get it right. You use AI agents and tools aggressively to multiply your output - writing code, exploring data, generating hypotheses, but you treat every AI-assisted output as a draft, not a deliverable. You know what good analysis looks like and you won't ship anything that doesn't meet that bar. The result is that you operate at a speed and depth that most DS teams can't match. You will: Design and analyze product experiments to evaluate feature launches, onboarding changes, and in-product interventions with rigorous statistical

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. Realizing that vision requires a platform that legitimate users can trust and adversarial actors cannot exploit. We're hiring a Data Scientist to help build Replit's Trust & Safety and Anti-Abuse program from the ground up. You'll turn noisy behavioral, identity, payment, infrastructure, and content signals into the measurement systems, detections, and decisions that protect Replit's users, platform, and economics. You'll work closely with Engineering, Support, Legal, Security, Infrastructure, Money, and Growth to make abuse economically unviable while keeping friction low for legitimate users. Replit sits at the frontier of AI-native abuse. Our platform is a target for phishing and scam hosting, cryptomining, LLM token farming, card and coupon fraud, referral abuse, and increasingly, abuse driven by AI agents themselves. You'll help define how we identify, measure, and respond to these threats without compromising the experience of good users. Who You Are You're a data scientist who moves fast, goes deep, and thinks adversarially. You can spin up an analysis in hours that would take others days, not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You dig past the top-line abuse rate to understand selection effects, missing labels, policy changes, attacker adaptation, and the false positives hidden inside an aggregate metric. You understand that Trust & Safety data is imperfect and outcomes are high stakes. Ground truth is delayed, biased, and often incomple

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . This role focuses on advancing the science and systems behind ML measurement, feature understanding, and causal inference at scale. The work spans areas such as production feature importance platforms, observational causal estimation in Pytorch, large-scale proxy metric development, and data-driven approaches to ML infrastructure efficiency. We're looking for an enthusiastic individual contributor to perform high-impact technical work across this space. This person will drive foundational innovations, own the end-to-end design of production ML systems, establish rigorous methodological standards, and partner cross-functionally to turn successful research into durable platform capabilities that raise the ceiling for the entire ML organization. What you’ll do: We are looking for an experienced and highly capable Data & Applied Scientist

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest brings millions of people the inspiration to create a life they love. Behind that experience is a complex infrastructure ecosystem that powers reliability, performance, measurement, and efficiency across the platform. As Pinterest grows, it’s increasingly important that we understand these systems clearly so we can make smarter decisions for both Pinners and the business. We’re looking for a Data Scientist to join our Infrastructure Data Science team. In this role, you’ll partner with engineering and cross-functional teams to make Pinterest’s infrastructure more measurable, intelligible, and actionable. Depending on the area, your work may span app performance, shopping infrastructure, metrics quality, infrastructure governance, or site reliability. You’ll help build the data foundations, measurement systems, and analytical fram

About the Team OpenAI’s Agentic Data Science team helps shape how AI agents are built, deployed, and improved across our products. We partner with product, engineering, research, and security teams to define meaningful measures of success, understand how our systems behave in the real world, and translate evidence into better decisions. As AI agents become more capable, they can write and execute code, access sensitive systems, and complete increasingly complex tasks with greater autonomy. These capabilities create powerful opportunities to improve cybersecurity, but they also introduce risks that traditional security tools and processes were not designed to address. Meeting this moment requires new ways to measure security, evaluate defenses, and distinguish genuine risk reduction from friction that slows users down. About the Role We are looking for a senior data scientist to help define what effective cybersecurity looks like in the age of AI agents. You will work across OpenAI’s Security organization and cybersecurity product teams to measure emerging risks, improve internal security controls, and shape AI-powered security products. The problems are foundational: How do we know whether an agent’s security controls are effective? Which safeguards meaningfully reduce risk, and which create unnecessary friction? When an AI system identifies a potential vulnerability, how do we determine whether the finding is accurate, actionable, and ultimately resolved? How do we detect anomalous behavior or risky access when the systems themselves are changing rapidly? You will report into Data Science while partnering closely with Security, Cyber Product, Engineering, and Research. This is a high-ownership role for someone who can establish a new analytical discipline, operate across organizational boundaries, and turn ambiguous security challenges into measurable improvements. In This Role You Will Define how we measure AI-agent security. Establish metrics and evaluation frame

About the Team The GTM Intelligence Solutions team builds the data and decision systems that help customer-facing teams take the right action at the right time. We combine product telemetry, commercial data, customer context, and field activity to identify account health and opportunity, recommend actions and use cases, deliver intelligence through field-facing products and agent workflows, and measure what happens next. We’re looking for a Data Scientist to help build the next generation of GTM intelligence at OpenAI. You will own a flexible portfolio of high-impact decision data products and work closely with Technical Success and other GTM teams to ensure the work drives better decisions. About the Role As a Data Scientist on GTM Intelligence Solutions, you will define and build the intelligence systems that help customer-facing teams prioritize accounts, identify risks and opportunities, choose interventions, and understand what worked. You will set the roadmap and methodology, build canonical features, ship reliable production workflows, monitor quality and adoption, and improve the systems using field feedback and business outcomes. This role combines hands-on technical depth with strong product and business judgment. You should be as comfortable writing production Python and advanced SQL, defining durable data contracts, and operating decision products as you are evaluating a ranking approach or designing an experiment. You will personally ship reliable first versions and partner with Analytics Engineering and Data Engineering when work requires shared infrastructure or additional scale. In This Role, You Will Set the roadmap and methodology for GTM intelligence and decision products, using deep stakeholder discovery to probe beyond stated requests, uncover the underlying decisions, workflows, constraints, and measures of success, and translate them into measurable systems. Own the full lifecycle of intelligence products, including feature definition, methodo

About the Role OpenAI's ads platform is experiencing rapid global scale. As the Lead Data Scientist for SMB Ads Growth, you will architect the analytics function end-to-end—driving strategy across targeting, funnel optimization, and performance forecasting. You will work directly with the SMB Ads Marketing team and your insights will be the primary catalyst for high-stakes decisions across marketing, product, and sales engineering. What You'll Do Full-Funnel Analytics Establish the foundational growth metrics and North Star KPIs for the SMB Ads ecosystem, optimizing the journey from lead acquisition to long-term retention. Diagnose funnel friction points through advanced behavioral analysis and quantify the incremental revenue impact of proposed optimizations. Partner cross-functionally to transform complex data findings into actionable, high-priority roadmaps for product and marketing stakeholders. Targeting, Segmentation & Propensity Modeling Engineer sophisticated propensity models and look-alike frameworks to identify and capture high-LTV SMB advertisers. Own the lifecycle of target list construction, including advanced data enrichment, multi-dimensional prioritization, and granular performance tracking. Develop robust segmentation architectures that power hyper-personalized outreach across paid, partnership, and outsourced (BPO) channels. Synthesize market signals to refine our value proposition, ensuring OpenAI remains a key platform for SMB business growth. Campaign Analytics & Measurement Design and implement rigorous multi-touch attribution and incrementality frameworks to evaluate channel efficacy. Lead the experimental roadmap: formulate hypotheses, execute A/B and multivariate tests, and communicate results to executive leadership. Automate business-critical reporting and dashboards to provide real-time visibility during weekly operating reviews. Forecasting & Planning Build high-fidelity revenue and advertiser growth models to project perfor

About the Role OpenAI's ads business is scaling quickly. As the Data Scientist for Ads Demand, you will build the measurement and insight foundation for understanding demand health and advertiser value across the marketplace. You will partner closely with Ads Sales leadership and Ads Product leadership—along with Marketing Science and product and sales teams—to diagnose advertiser performance, define benchmarks, identify growth opportunities, and turn advertiser feedback into product priorities. Your work will shape demand strategy, improve advertiser outcomes, and help OpenAI build for its most valuable advertisers. What You'll Do Demand Health & Measurement Define the North Star metrics, diagnostic framework, and measurement strategy for demand health across the ads system. Build the operating view of demand across spend, active advertisers, retention, budget utilization, delivery, concentration, and mix; identify emerging risks and opportunities. Diagnose changes in demand through cohort analysis, decomposition, experimentation, and causal methods, translating findings into clear actions for Sales and Product leadership. Advertiser Performance & Benchmarks Own the end-to-end view of advertiser outcomes—including delivery, ROAS, conversion performance, retention, and budget efficiency—for individual advertisers and key cohorts. Establish actionable benchmarks by objective, vertical, advertiser size, geography, maturity, and product adoption, with statistically sound peer comparisons. Develop early-warning signals and opportunity scoring that help sales teams surface under-delivery, performance risk, and advertiser growth potential. Set standards for metric definitions, data quality, and interpretation so leaders can separate real marketplace changes from seasonality, selection effects, and measurement artifacts. Insights, Adoption & Advertiser Feedback Partner with Marketing Science, Sales, and Product to translate analysis into credible advertiser-fac

About the Team OpenAI’s GTM Data Science team helps shape how our products are adopted, monetized, and scaled across organizations. We work at the intersection of Product, Go-to-Market, Finance, Research, and Data, turning product usage, customer evidence, and market signals into decisions that grow durable enterprise value. We’re looking for a senior Data Scientist to own the analytical strategy for enterprise knowledge-worker adoption. As ChatGPT Work and Codex become capable of research, analysis, document creation, spreadsheets, presentations, internal knowledge synthesis, and other agentic workflows, you will help determine how these products become embedded in everyday work—not merely tried once. About the Role You will define how we measure activation, retained usage, workflow depth, and value across ChatGPT Work, Codex, and connected enterprise systems. You will explain why adoption succeeds or stalls and identify the product, enablement, and commercial interventions most likely to create durable usage. This is a hands-on, zero-to-one role. You will work through imperfect telemetry, overlapping product surfaces, evolving definitions, and ambiguous business questions. You will partner closely with GTM, Product, Finance, Research, Customer Deployment, Analytics Engineering, and Data Science. Your work is successful when it changes a product, GTM, or investment decision. In This Role, You Will Define a trusted measurement framework for knowledge-worker adoption, including identity, eligible populations, activation, retained usage, penetration, workflow depth, feature adoption, and monetization. Map the knowledge-worker journey from initial exposure through first successful task, repeated workflows, multi-surface usage, and durable adoption. Identify which personas, functions, use cases, product capabilities, and account conditions are associated with deep and retained usage. Design and evaluate experiments and quasi-experiments across onboarding, enablement, wo

About the Team OpenAI’s Financial Engineering and Identity data science team owns how revenue flows through our products and builds the systems that enable people and organizations to access OpenAI products safely, seamlessly, and at global scale. Identity sits at the critical intersection of growth, trust, and user experience. The team owns the experiences and infrastructure behind sign up, sign in, account recovery, authentication, and identity integrations across both consumer and enterprise products. As OpenAI expands across products and markets, Identity plays an increasingly important role in helping more users get started quickly while protecting them from abuse, fraud, and account compromise. About the Role We're looking for the first dedicated Data Scientist to partner with the Identity organization. In this role, you will define how we measure success across the entire identity journey—from first-time sign up and onboarding through authentication, account recovery, and enterprise identity experiences. You'll develop the experimentation frameworks, metrics, and analytical approaches that guide product decisions while helping the team navigate one of Identity's core challenges: optimizing growth while maintaining trust and security. You'll work closely with Product, Engineering, Design, Abuse, Risk, and Go-to-Market teams to identify opportunities, quantify trade-offs, and influence strategy. Some questions can be answered through A/B tests. Others require observational analyses, causal inference, and judgment under uncertainty. This is an opportunity to shape the analytical foundations of a high-impact product area from the ground up. This role is based in San Francisco, CA. We use a hybrid model (3 days/week in office) and offer relocation support. In this role, you will Define the north-star metrics and measurement frameworks used to evaluate the identity experience across consumer and enterprise products. Design and analyze experiments to optimize top-of

By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We expect you to: Have 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 or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for