Senior Machine Learning Data Scientist (Forecasting)

Location: San Francisco, United States. Hybrid work model with 3 days in the office per week. Relocation assistance is available to new employees.

Salary: $347,000–$445,000 base pay annually, plus equity, performance-related bonuses, and benefits.

Company

OpenAI is an AI research and deployment company developing and safely deploying general-purpose artificial intelligence products.

What you will do

• Build statistical and machine learning forecasting models across product, finance, infrastructure, and go-to-market domains.
• Own the end-to-end modeling lifecycle, including scoping, feature engineering, development, prototyping, experimentation, deployment, monitoring, debugging, maintenance, and explainability.
• Develop and productionize scalable, interpretable forecasts for user growth, monetization, compute load, customer lifetime value, and profitability.
• Contribute to self-service forecasting tools and internal platforms that provide real-time predictions to teams across OpenAI.
• Research forecasting techniques including TimeGPT, large language model extensions, causal forecasting, and hybrid approaches.
• Translate technical outputs into business recommendations and decision frameworks while integrating forecasts into planning, experimentation, and executive decision-making.

Requirements

• Advanced degree (MS or PhD) in a quantitative field, such as Statistics, Computer Science, Economics, or Operations Research.
• 7+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems.
• Expertise in time-series forecasting techniques and practical understanding of trade-offs among performance, explainability, and scalability.
• Proficiency in Python and SQL, plus tools such as scikit-learn, PyTorch or TensorFlow, and forecasting libraries.
• Experience with model monitoring, debugging, and long-term maintenance in production environments.
• Strong communication and storytelling skills, including the ability to simplify complex topics and influence executive stakeholders.
• Ability to work independently, demonstrate intellectual curiosity, and lead ambiguous projects from 0 to 1.

Nice to have

• Experience building or scaling forecasting platforms in a high-growth company.
• Familiarity with causal inference and Bayesian forecasting.
• Experience building agentic decision-support systems.
• Passion for AI and a strong point of view on how machine learning should inform strategic decisions in fast-moving environments.

Culture & Benefits

• Close collaboration with Product, Engineering, Go-To-Market, research, and finance leaders.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• 401(k) retirement plan with employer match, flexible or accrued paid time off, paid holidays, paid parental and caregiver leave, and paid sick or safe time.
• Mental health and wellness support, life and disability coverage, and an annual learning and development stipend.
• Daily office meals, eligible meal delivery credits, commuter benefits, relocation support, and additional taxable fringe benefits.

Hiring process

• More detailed benefits information is provided during the hiring process.
• Background checks are administered in accordance with applicable law.