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Machine Learning Data Scientist – Forecasting
| Company | OpenAI |
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| Location | San Francisco, CA, USA |
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| Salary | $255000 – $405000 |
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| Type | Full-Time |
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| Degrees | Master’s, PhD |
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| Experience Level | Senior, Expert or higher |
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Requirements
- Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, 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 model trade-offs across performance, explainability, and scalability
- Proficiency in Python, SQL, and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries
- Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments
- Strong communication and storytelling skills – able to simplify complexity and influence executive stakeholders
- Self-directed, intellectually curious, and comfortable leading ambiguous projects from 0→1
Responsibilities
- Build time-dependent statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains
- Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, 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, enabling teams across OpenAI to access and act on real-time predictions
- Research and evaluate emerging tools and techniques in the forecasting space, such as TimeGPT, large language model extensions, causal forecasting, and hybrid approaches
- Drive strategic insight generation by translating technical outputs into business-aligned recommendations and decision frameworks
- Collaborate closely with cross-functional teams to ensure forecasts are well-integrated into planning processes, experimentation workflows, and executive decision-making
Preferred Qualifications
- Experience building or scaling forecasting platforms in a high-growth company
- Familiarity with causal inference, Bayesian forecasting
- Passion for AI and a strong point of view on how machine learning should inform strategic decisions in fast-moving environments
