Applied Data Scientist, Personalization & Machine Learning

We work across product, growth, and monetization to help people get more value from OpenAI’s products. We identify opportunities for machine learning, build and test early solutions, and partner with engineering and product to bring successful approaches into production.

We’re looking for a data scientist who can enter an unfamiliar product area, find a useful ML application, and turn it into a working product intervention. You will own the work from problem definition and data preparation through modeling, experimentation, and launch evaluation.

Projects will include personalization, next-best-action recommendations, lifecycle management, promotion targeting, and models of retention and customer lifetime value. You will help identify opportunities, build proofs of concept, evaluate, and iterate.

In this role, you will:

• Identify opportunities with product and business partners, define the decision a model will inform, and prioritize work by user value, feasibility, and expected impact.
• Build datasets, features, reproducible training workflows, and models. You’ll use a combination of tools appropriate to the task at hand.
• Translate predictions into product actions. Design experiments and use causal reasoning to establish whether those actions improve user and business outcomes.
• Partner with engineers on integration, serving or batch scoring, monitoring, and rollout. Stay involved through launch and iteration.
• Explain results and limitations clearly, document decisions, and build reusable methods that other teams can adopt.

You might thrive in this role if you:

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