Data Scientist, Personalization – Machine Learning

OpenAI

. Identify opportunities with product and business partners .

Posted 10/26/2026full-timeSan Francisco • California • United StatesMid-LevelSenior💰 $347,000 - $445,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and evaluating applied machine learning systems that drive product and business decisions, with a strong focus on data-driven experimentation and personalization strategies. Proficient in Python and SQL, with experience in developing production scoring pipelines and understanding of recommendation systems.

Highest-signal resume keywords

Applied Machine Learning SystemsPython ProgrammingSQL ProficiencyProduction Scoring PipelinesRecommendation Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData AnalysisFeature EngineeringCausal ReasoningModel EvaluationSupervised LearningExperiment DesignDebugging ModelsPersonalizationTreatment-Effect Modeling

Soft Skills

Problem-SolvingCross-Disciplinary CollaborationClear Communication

Tools & Technologies

DbtAirflowFlyte

Industry Keywords

User ValueBusiness OutcomesCustomer Lifetime ValueRetentionNext-Best-Action Recommendations

Tech Stack

Tools & technologies

AirflowPythonSQL

About the role

Key responsibilities & impact

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
Translate predictions into product actions
Design experiments and use causal reasoning to establish whether 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 for other teams
Work on personalization, next-best-action recommendations, lifecycle management, promotion targeting, retention, and customer lifetime value models

Requirements

What you’ll need

Experience building and evaluating applied ML systems that influenced a product or business decision, with clear ownership of modeling work
Effective Python and SQL skills
Ability to investigate imperfect data, debug models, and make pragmatic implementation choices
Experience building and scheduling production scoring pipelines using dbt, Airflow, and Flyte
Understanding of supervised learning, evaluation, experimentation, and the difference between predicting an outcome and changing it
Ability to scope ambiguous problems, work across disciplines, and explain technical tradeoffs
Experience with recommendation systems, personalization, growth, retention, lifetime value, or treatment-effect modeling would be useful
Ability to work from the San Francisco office three days per week
Authorization to work in the country where the job is located

Benefits

Comp & perks

Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents)
Paid medical and caregiver leave (up to 8 weeks)
Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays
Multiple paid coordinated company office closures throughout the year for focus and recharge
Paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend
Daily meals in offices, and meal delivery credits as eligible
Relocation support for eligible employees
Charitable donation matching and wellness stipends may also be provided
Equity
Performance-related bonuses for eligible employees