Applied ML Scientist — Personalization & Next-Best-Action

OpenAI, Inc.; San Francisco (CA); Presencial; USD 150.000 - 210.000; Tempo integral

Resumo da vaga

OpenAI, Inc. is seeking a data scientist to tackle unfamiliar product areas, define problems, and turn ML ideas into operational interventions.

You will own the work from data preparation through modeling, experimentation, and launch evaluation, collaborating with product and engineering to drive impact on retention and customer lifetime value. We are looking for someone who can build and evaluate applied ML systems, write Python and SQL, and deploy end-to-end scoring pipelines.

Qualificações

• Applied ML systems with ownership over modeling work.
• Investigate imperfect data, debug models, and deploy pragmatic solutions.
• Familiarity with recommender or personalization domains is a plus.

Responsabilidades

• 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.

Conhecimentos

Python

SQL

Experimentation

Causal reasoning

Modeling

Production deployment

Ferramentas

dbt

Airflow

Flyte

Descrição da vaga

OpenAI, Inc. is seeking a data scientist to tackle unfamiliar product areas, define problems, and turn ML ideas into operational interventions.

You will own the work from data preparation through modeling, experimentation, and launch evaluation, collaborating with product and engineering to drive impact on retention and customer lifetime value. We are looking for someone who can build and evaluate applied ML systems, write Python and SQL, and deploy end-to-end scoring pipelines.