Founding Data Scientist, Pricing & Monetization
Founding Data Scientist on OpenAI's Pricing team, building analytical foundations and models for pricing, packaging, and monetization strategy across consumer, SMB, and enterprise segments. Partner directly with CFO and senior leaders on high-impact analyses, experiments, causal inference, and executive recommendations in a zero-to-one role.
About the job
Responsibilities
- Serve as a senior analytical partner to the CFO, Head of Pricing, Product, and GTM leaders on pricing and monetization decisions.
- Build the analytical foundation for pricing across consumer, SMB, and enterprise segments, from exploratory analysis to repeatable decision systems.
- Design and execute analyses that connect customer behavior, product usage, conversion, retention, revenue outcomes, and pricing strategy.
- Develop models, algorithms, experiments, and decision frameworks for complex pricing, packaging, discounting, and willingness-to-pay questions.
- Translate technical work into crisp executive recommendations and practical operating guidance for cross-functional teams.
- Identify where a dedicated pricing data science function can create repeatable leverage, helping define the roadmap, standards, and future operating model for the team.
Requirements
- Significant experience in data science, analytics, economics, statistics, machine learning, or a related quantitative field.
- Strong technical ability in analysis, modeling, experimentation, causal inference, and data-driven decision-making.
- Experience working on pricing, monetization, marketplace dynamics, usage-based pricing, dynamic pricing, packaging, or adjacent high-complexity business problems.
- Ability to operate independently in ambiguous environments, define analytical direction from scratch, and bring senior stakeholders along through clear tradeoff framing.
- Strong written and verbal communication skills, including the ability to influence executive-level audiences and cross-functional operating teams.
Nice-to-Haves
- Prior pricing experience across consumer, SMB, enterprise, marketplace, platform, or AI/API businesses.
- Experience building novel pricing models, systems, experimentation programs, or decision frameworks.
- PhD preferred; a master’s degree or equivalent practical experience can also be a strong fit.
- Experience helping establish a new data science function, operating model, technical roadmap, or executive decision cadence.
- Deep experience using causal inference and other statistical techniques to solve pricing, monetization, packaging, or business strategy problems.
Skills
Causal Inference, Statistical Modeling, Experimentation, Pricing Models, Machine Learning, Data Analysis, Python, SQL, A/B Testing, Willingness-To-Pay Analysis, Dynamic Pricing, Usage-Based Pricing
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