Jobs / United States / OpenAI UK Ltd
Data Scientist, B2B Generalist
OpenAI UK Ltd · 🇺🇸 San Francisco
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- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
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Sponsor Radar — OpenAI UK Ltd
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About the role
About the Role We are hiring a Data Scientist to help build OpenAI's B2B ecosystem and go-to-market data science capability. You will turn ambiguous commercial questions into evidence, recommendations, and operating decisions that help OpenAI understand where to focus as our B2B business expands. OpenAI's B2B motion is growing quickly across products, customer segments, markets, and field teams. This role will partner with leaders across GTM, Revenue, Product, Finance, RevOps, Strategy, and Data Science to answer questions tied to international strategy, monetization, product penetration, field deployment, customer opportunity, and organizational design. This is a founding-style opportunity within the broader GTM Data Science organization. The team and stakeholder model are still evolving, so you should be energized by building structure in ambiguity, helping define how the team works, and helping shape the bench around a high-priority commercial area. In this role, you will bring data science craft, consulting-style problem solving, practical AI fluency, and strong business judgment to help senior leaders make better B2B decisions. In this role, you will: - Structure ambiguous B2B and go-to-market questions into clear operational plans, identifying the decision at stake, the evidence needed, and how insights will translate into action. - Lead strategic deep dives across international expansion, monetization, product penetration, customer segmentation, field deployment, ecosystem dynamics, and organizational design. - Analyze product usage, customer behavior, adoption patterns, sales and field activity, pipeline and revenue signals, and market context to identify the drivers of B2B growth. - Partner closely with GTM, Revenue, Product, Finance, RevOps, Strategy, and Data Science leaders to turn analysis into prioritization decisions, field plays, investment choices, and operating cadences. - Communicate complex findings to executives and cross-functional partners with crisp recommendations, transparent assumptions, and clear tradeoffs. - Bring practical AI fluency to the work, using modern AI tools to accelerate analysis, synthesize evidence, improve workflows, and identify new ways data science can support business decision-making. - Help define the operating model for an emerging B2B data science capability, including how the team frames problems, engages stakeholders, evaluates opportunities, and turns insights into GTM action. You might thrive in this role if you have: - Senior-level experience in a quantitative role such as Data Science, Product Analytics, Decision Science, Growth Analytics, Strategy Analytics, or a related field. - Strong business judgment and a track record of translating ambiguous analytical work into decisions that business leaders can act on. - Experience working on B2B,, GTM or commercial strategy, monetization,, product growth, or similarly complex business problems. - Strong technical fluency with analytical tools such as SQL and Python, or equivalent experience using data to answer open-ended business questions. - Ability to connect data across product, customer, sales, revenue, market, and operational contexts to form a coherent view of the business. - Consulting-style problem solving: you can structure a broad question, identify the highest-leverage analysis, manage uncertainty, and communicate a practical recommendation. - Excellent executive communication and cross-functional partnership. You can influence senior leaders, field teams, product partners, operators, and other data scientists with clear evidence and balanced judgment. - Comfort operating in a high-ambiguity, fast-changing environment where the team, roadmap, and stakeholder model are still taking sh