Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
Communication @ 6
Data Science @ 4
Python @ 7
SQL @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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 its B2B business expands.
OpenAI's B2B motion is growing across products, customer segments, markets, and field teams. This role partners with leaders across GTM, Revenue, Product, Finance, RevOps, Strategy, and Data Science on questions related 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 the role requires building structure amid ambiguity, defining how the team works, and helping shape the team around a high-priority commercial area.
Responsibilities
- 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 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 concise recommendations, transparent assumptions, and clear tradeoffs.
- Use 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.
Requirements
- 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 with 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, including structuring broad questions, identifying high-leverage analyses, managing uncertainty, and communicating practical recommendations.
- Excellent executive communication and cross-functional partnership skills, with the ability to influence senior leaders, field teams, product partners, operators, and other data scientists.
- Comfort operating in a high-ambiguity, fast-changing environment where the team, roadmap, and stakeholder model are still taking shape.
- Practical AI fluency and curiosity about how modern AI tools can improve analytical workflows, strategic synthesis, and decision support.
- Experience in strategy consulting followed by data science work in technology, or data science work within a consulting analytics practice, is a strong plus.
- An advanced degree is welcome but not required; analytical rigor, business judgment, and action-oriented communication are valued most.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. OpenAI is an equal opportunity employer and does 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.
Background checks for applicants will be administered in accordance with applicable law. OpenAI is committed to providing reasonable accommodations to applicants with disabilities.
Benefits
- Base salary range of $347,000–$445,000, plus equity.
- Medical, dental, and vision insurance for employees and their families, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for health, dependent care, and commuter expenses.
- 401(k) retirement plan with employer match.
- Paid parental, medical, and caregiver leave.
- Paid time off, paid company holidays, office closures, and paid sick or safe time as required by applicable law.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily office meals and eligible meal delivery credits.
- Relocation support for eligible employees.
- Additional taxable fringe benefits may include charitable donation matching and wellness stipends.