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Machine Learning Data Scientist, Forecasting - OpenAI

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Job Title
Machine Learning Data Scientist, Forecasting
Job Location
San Francisco
Job Description

About the Team

The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.

We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential.

About the Role

We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability.

This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

  • 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.

You might thrive in this role if you have:

  • 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.

Bonus if you have:

  • 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.

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 do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status. 

OpenAI Affirmative Action and Equal Employment Opportunity Policy Statement

For US Based Candidates: Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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OpenAI Headquarters Location

San Francisco, CA

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OpenAI Company Size

Between 500 - 800 employees

OpenAI Founded Year

2015

OpenAI Total Amount Raised

$61,900,120,064

OpenAI Funding Rounds

View funding details
  • Series Unknown

    $40,000,000,000 USD

  • Debt Financing

    $4,000,000,000 USD

  • Series Unknown

    $6,600,000,000 USD

  • Secondary Market

    $300,000,000 USD

  • Corporate Round

    $10,000,000,000 USD

  • Corporate Round

    $1,000,000,000 USD

  • Pre Seed

    $120,000 USD