Data Scientist, Growth (AI)

Location: New York City, NY; Seattle, WA; or San Francisco, CA. Hybrid policy: staff are expected to work from one of the offices at least 25% of the time, with some roles requiring more office attendance.

Annual salary: $285,000–$380,000 USD.

Company

Build reliable, interpretable, and steerable AI systems intended to be safe and beneficial for users and society.

What you will do

• Build and ship targeting and personalization models that select messages, offers, and product experiences for users in collaboration with growth product managers and engineers.
• Design and evaluate personalization strategies using holdouts, contextual bandits, and off-policy estimates where A/B testing is impractical.
• Design and analyze A/B tests and quasi-experiments across activation, retention, and monetization, translating results into recommendations.
• Develop metrics and guardrails that connect short-term results with long-term value.
• Use Claude to support analysis, reporting, experimentation, and new analytical workflows.

Requirements

• Experience applying data science to growth, lifecycle, or personalization problems.
• Experience building and shipping machine learning models that drive user-facing decisions, including targeting, ranking, recommendation, or personalization.
• Experience with experimental design and causal inference, including A/B testing at scale, holdouts, and quasi-experimental methods.
• Proficiency in Python and SQL.
• Experience communicating analysis in writing and making recommendations that influence priorities across teams.
• Ability to prioritize and make progress when requirements are unclear or changing.
• Interest in building safe and beneficial AI.
• Bachelor’s degree or an equivalent combination of education, training, and experience in a relevant field demonstrated through coursework, training, or professional experience.

Nice to have

• 7+ years of experience in data science.
• Experience running contextual bandits, uplift models, or similar decision systems in production.
• Experience with lifecycle or CRM personalization, including email, push, and in-product messaging, and measurement challenges such as global holdouts and campaign interference.
• Experience defining activation metrics and lifecycle measurement for a product-led business.
• Experience with experimentation platforms and meta-analysis across experiment portfolios.
• Experience with consumption-based, multi-product businesses serving consumers and enterprises.
• Experience using LLMs or coding agents in analytical workflows.

Culture & Benefits

• Collaborative work across research, engineering, policy, and business disciplines.
• Flexible working hours and office-based collaboration.
• Competitive compensation, optional equity donation matching, generous vacation, and parental leave.
• Visa sponsorship may be available, with immigration lawyer support, subject to role and candidate eligibility.
• Emphasis on diverse perspectives, communication, research discussions, and high-impact AI work.