Applied Data Scientist, Personalization & Machine Learning
Applied Data Scientist, Personalization & Machine Learning
Posted 2 days ago
SENIORITY
Senior
About the role
- 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:
- Have built and evaluated applied ML systems that influenced a product or business decision, with clear ownership of the modeling work.
- Write effective Python and SQL and can investigate imperfect data, debug models, and make pragmatic implementation choices.
- Build and schedule production scoring pipelines using dbt, airflow, and flyte.
- Understand supervised learning, evaluation, experimentation, and the difference between predicting an outcome and changing it.
- Can scope ambiguous problems, work across disciplines, and explain technical tradeoffs to colleagues with different backgrounds.
- Are motivated by helping people use AI effectively and by learning unfamiliar product domains.
- Are excited to take on challenging, impactful ML problems across multiple areas.
- Have experience with recommendation systems, personalization, growth, retention, lifetime value, or treatment-effect modeling would be useful. We welcome candidates whose relevant experience comes from other domains.
- About OpenAI
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
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A number in mind
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Your notice period
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