The opportunity
Cloud service providers give developers a way to use OpenAI models in the environments where they already build and run software. Our team works with Go-to-Market (GTM), Product, Engineering, and Finance to understand which customers we can reach through these providers and what…
What you'll do
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 contribute to growth.
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. Work with Product and Engineering on a change and measure what happens to usage.
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 where to focus with each provider.
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.
Like questions that take you from a conversation with an account team to a: query about a single API request. You’re curious about why a customer’s behavior differs from what the numbers first suggest.
What they're looking for
- Are comfortable making a recommendation while some questions are still open.: You can tell a sales leader where you’d invest and explain to an engineer what evidence would change your mind.
- 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 forecast against a simple baseline.