Data Scientist, Cloud Distribution & Growth

Job summary

Responsibilities

In your first few months, you’ll identify a customer segment or workload where OpenAI can grow, recommend an investment to GTM, Product, and Engineering, and define how we’ll know whether it brought new usage to OpenAI.

• Build a reliable view of the business from provider usage reports, billing records, and API logs. Show how new workloads, expansion, changes in price, and shifts in model mix…
• Estimate how much demand cloud distribution adds to OpenAI. Trace customer activity across channels to distinguish new use cases from traffic that moved from the direct API.
• Identify where customers are ready to scale. Combine what account teams hear with evidence on request failures, latency, and model availability.
• Shape growth plans with GTM and Finance. Estimate what existing workloads and upcoming launches can contribute by year end, test the assumptions that matter most, and recommend…
• Own the consumption forecast. Compare forecasts with actual usage over the same period, explain the biggest misses, and use what you learn to improve the next forecast.

What they're looking for

• Experience independently leading data science work on a product, growth, or commercial question that changed a business decision.
• Strong SQL and Python skills. You can join incomplete datasets, choose the right unit of analysis, and validate an aggregate result against individual customers or workloads.
• Experience using cohorts, experiments, or observational comparisons to assess what drove a change. You can explain how customer selection affects the conclusion and evaluate a…
• Experience with API platforms, cloud marketplaces, enterprise GTM, or a usage-based business.
• Experience connecting service reliability or capacity to customer adoption, or using demand forecasts to guide a commercial or infrastructure investment.

Tech stack

• SQL
• Python