Nuvepro - Task Intelligence for the Enterprise
OpenAI· Data Science· San Francisco

Data Scientist, ChatGPT for Work

Comp$293K – $515K

Classified Tasks (18)

Automate 0%Augment 78%Human-Only 22%

Augment (14)

AI assists, human decides

Uncover the user problems most worth solving through data analysis

analytical

Form sharp hypotheses about actions that will move team and business outcomes

analytical

Influence product decisions by presenting recommendations grounded in rigorous evidence

leadership

Define what “success” means for teams across Work product experiences

analytical

Pinpoint highest-leverage adoption and retention bottlenecks for individuals and teams

analytical

Turn product and usage signals into clear product direction and roadmap priorities

leadership

Ensure experimentation is designed and executed with rigorous methodology

analytical

Own the core KPI framework spanning onboarding, activation, engagement, retention, expansion, and quality/trust guardrails

operational

Build end-to-end funnels that identify where individuals and teams succeed or get stuck from initial setup through long-term adoption

analytical

Define and operationalize “time-to-value” and collaboration loop metrics and connect them to business outcomes

analytical

Design and evaluate experiments and rollouts to quantify the impact of product changes across key Work surfaces and flows

analytical

Partner with product and engineering teams to improve instrumentation, data quality, and metric definitions

technical

Translate complex analyses into clear, compelling insights that shape product strategy and roadmap decisions

communication

Help establish data science standards and best practices for measuring human–AI collaboration and AI-native work outcomes

technical

Human-Only (4)

Requires human judgment

Own the insight → strategy → experiment → decision loop for ChatGPT for Work

leadership

Partner with Product, Engineering, Research, and Finance to align on metrics and decisions

operational

Ensure insights translate into shipped product improvements

operational

Partner with other data scientists across the company to share learnings and raise the bar on measurement, experimentation, and decision-making

leadership

Job description

Data Scientist, ChatGPT for Work | OpenAI Careers ## Data Scientist, ChatGPT for Work Data Science - San Francisco Apply now(opens in a new window) **About the Team** OpenAI’s mission is to ensure AI benefits all of humanity. ChatGPT for Work supports that mission by helping more people access real leverage from AI in their day-to-day jobs—so they can spend less time on busywork and coordination, and more time on the work that’s meaningful and additive. We’re building an AI-native workspace where AI acts as a superassistant for everyday tasks and a coworker you can hand work off to—then review, edit, and approve with confidence. And we’re doing it in a way organizations can trust, by grounding experiences in the right company context and systems safely and reliably. **About the Role** As the Data Scientist for ChatGPT for Work, you’ll shape product strategy through data: uncover the user problems most worth solving, form sharp hypotheses about what will move team and business outcomes, and influence what we build next by presenting compelling recommendations grounded in rigorous evidence. You’ll be the DRI for the Work **insight → strategy → experiment → decision** loop—defining what “success” means for teams, pinpointing the highest-leverage adoption and retention bottlenecks, and turning signals into clear product direction. You’ll partner closely with Product, Engineering, Research, and Finance to ensure our metrics are trusted, our experimentation is rigorous, and our insights turn into shipped improvements. This role is based in San Francisco. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. **In this role, you will:** * Own the core KPI framework for ChatGPT for Work, spanning onboarding, activation, engagement, retention, and expansion, as well as quality/trust guardrails. * Build end-to-end funnels that identify where individuals and teams succeed or get stuck, from first workspace setup through repeat usage and long-term team adoption and value creation. * Define and operationalize “time-to-value” and collaboration loop metrics, and connect them to business outcomes. * Design and evaluate experiments and rollouts to quantify the impact of product changes across key Work surfaces and flows. * Partner with product and engineering teams to improve instrumentation, data quality, and metric definitions so decisions are fast and correct. * Translate complex analysis into clear, compelling insights that shape product strategy and roadmap decisions. * Help establish data science standards and best practices for measuring human–AI collaboration and AI-native work outcomes. * Partner with other data scientists across the company to share learnings and raise the bar on measurement, experimentation, and decision-making. **You might thrive in this role if you have:** * 10+ years in data science / analytics in in high-velocity product environments * Direct experience working on B2B products (SaaS, collaboration/workspace, developer tools, or enterprise) * Expert SQL + strong Python * Strong experimentation + causal inference judgment (incl. when clean A/B tests aren’t feasible) * Strong product sense/taste: can turn messy signals into crisp hypotheses and roadmap direction * Proven ability to inspire and influence PM/Eng/Design + leadership through data storytelling * Autonomous operator who sets the insights/measurement agenda * Excellent executive communication; thrives in ambiguous, fast-moving environments * AI-native operator (non-negotiable): “super AI-pilled”—first to adopt new AI tools, uses them daily to increase throughput, and turns them into durable org workflows **Nice-to-haves** * Experience with agentic and/or AI-native B2B products (agents, copilots, workflow automation, AI collaboration) * Experience measuring AI product quality, trust, and human-AI interaction signals * Familiarity w
Source: OpenAI careers · scraped 2026-05-22
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