Data Scientist, B2B Demand Generation, Growth & Measurement

Job Description: Data Scientist, B2B Demand Generation, Growth & Measurement About the Role We are hiring a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will help us understand which marketing investments create incremental demand, qualified pipeline, and revenue and how to scale them efficiently. Our mandate is to build a rigorous, full-funnel view of how B2B marketing creates demand and moves prospects from awareness and engagement to qualified opportunities, closed-won revenue, and expansion. You will shape how we measure marketing impact and influence across channels, campaigns, audiences, and account segments. In this role, you will partner closely with B2B Marketing, Demand Generation, Growth, Sales, RevOps, Finance to connect marketing activity to qualified pipeline, customer acquisition, and efficient revenue growth. What You’ll Do - Define north-star, leading, and guardrail metrics for B2B demand generation, including account engagement, qualified leads and opportunities, sourced and influenced pipeline, conversion rates, pipeline velocity, and incremental ARR. - Design and execute measurement and experimentation strategies across channels and campaigns, using randomized tests, audience or geographic holdouts, lift studies, quasi-experimental methods, and other causal approaches suited to long B2B sales cycles. - Analyze channel, audience, campaign, creative, content, landing-page, and account-segment performance to identify the drivers of qualified demand, funnel conversion, pipeline quality, and incremental revenue. - Partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve instrumentation, campaign taxonomy, CRM data quality, lead-to-account matching, and the operating cadence for acting on measurement insights. - Build AI-native measurement and decision-support workflows, using LLMs and agents to synthesize campaign performance, surface growth opportunities, and help marketers act on evidence at scale. What We’re Looking For - 10+ years in a quantitative role such as Data Science, B2B Demand Gen Marketing Science, Growth Analytics, Decision Science, with meaningful experience supporting B2B marketing, demand generation, pipeline growth, or enterprise and SMB go-to-market motions. - Deep expertise in experimentation, causal inference, and applied statistics, including incrementality testing and measurement strategies for multi-touch marketing journeys, limited observability, and long or heterogeneous sales cycles. - Strong technical fluency in SQL and Python, with experience joining and analyzing marketing-platform, web analytics, product, CRM, account, opportunity, and revenue data to produce reliable business insights. - Proven ability to translate analysis into marketing decisions, including channel and audience prioritization, campaign optimization, funnel improvements, budget allocation, forecasting, and go-to-market strategy. - Strong business judgment and a bias toward action. - Strong understanding of B2B funnel mechanics, account-based buying journeys, sales handoffs, lead and opportunity qualification, attribution tradeoffs, instrumentation, and the relationship between marketing investment, pipeline, and revenue. - Excellent communication and cross-functional partnership. You can influence marketers, sales and finance leaders, data scientists, product managers, and engineers with clear recommendations, credible evidence, and transparent tradeoffs. - AI-native mindset and hands-on experience using LLMs, agents, and modern AI tools to automate analysis, accelerate experimentation, and build scalable decision-support workflows. 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 applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candi

10+ years in a quantitative role such as Data Science, Product Analytics, Decision Science, or Applied Statistics, ideally at a product-led company supporting B2B growth, revenue systems, sales, lifecycle, or scaled self-serve motions. Deep grounding in experimentation, causal inference, and applied statistics, with experience designing and interpreting tests in real-world, always-on environments. Strong technical fluency in SQL and Python, including working directly with messy, incomplete operational and behavioral data to extract signal and quantify impact. Proven track record translating analysis into shipped decisions, not just readouts: changes to product, routing, targeting, automation, policy, workflow design, or GTM strategy. Strong business judgment and a bias toward action. You can scope ambiguous problems, define success, choose the highest-leverage measurement path, and move quickly from insight to decision. Systems thinking and technical maturity. You can reason about agents, workflows, instrumentation, data quality, human review, feedback loops, and operational constraints together. Excellent communication and cross-functional partnership. You can influence PMs, engineers, GTM operators, DS peers, and senior leaders with clear recommendations and practical tradeoffs.