Product Data Scientist
Remote • San Francisco • FullTime
Posted 6h ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Baseten powers mission-critical inference for leading AI companies, enabling them to bring cutting-edge models into production. We are seeking a Product Data Scientist to establish how Baseten leverages data for product decisions. This foundational, hands-on role involves defining success metrics, designing and analyzing experiments, and translating open-ended questions into actionable insights, forecasts, and analyses using diverse data sources like clickstream, product events, and inference telemetry. You will collaborate closely with founders, Product, Engineering, and GTM teams to shape product strategy and drive decisions on reliability, performance, adoption, and developer experience.
Responsibilities
- Partner with Product and Engineering to define key questions, success criteria, and translate analysis into roadmap, launch, and prioritization decisions.
- Define product success metrics across activation, adoption, retention, expansion, reliability, and user experience.
- Design measurement plans for launches, analyze A/B experiments and controlled rollouts, and translate results into product decisions.
- Map the enterprise customer journey and measure feature adoption at each stage.
- Evaluate releases and recovery by measuring traffic shifts, analyzing warm-up, drain, probe, and rollback behavior, and tracking MTTR and self-serve incident outcomes.
- Analyze customer and cohort behavior and share clear recommendations.
- Build source-of-truth reporting and self-serve tools for cross-functional use.
Requirements
- 5+ years of experience in product data science, product analytics, or a similar quantitative role, preferably supporting developer platforms, APIs, or B2B products.
- Deep SQL and Python fluency with experience analyzing large event-level datasets and producing decision-ready work.
- Strong statistical judgment and hands-on experimentation experience, including test design, power analysis, and knowing when directional evidence is sufficient.
- Hands-on forecasting experience with ARIMA, Prophet, or comparable time-series methods, including disciplined backtesting, error analysis, and scenario planning.
- Experience designing medallion data architectures, including raw, conformed, and business-ready models with testing, documentation, and lineage.
- Familiarity with dbt, semantic layers, data ontology, and BI tools such as Sigma or Hex.
Benefits
- Competitive compensation
- Meaningful equity
- 100% coverage of medical, dental, and vision insurance for employee and dependents (U.S. only)
- Flexible PTO policy
- Company-wide Winter Break
- Paid parental leave
- Fertility and family-building stipend
- Company-facilitated 401(k) (U.S. only)
- Exposure to a variety of ML startups for learning and networking opportunities