Product Data Scientist

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We're hiring a Product Data Scientist to establish how product decisions at Baseten are made with data. You'll work directly with Product and Engineering, alongside GTM to determine measurement, strategy, experimentation and implementation. This is a foundational, hands-on role. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape product strategy. You'll work from clickstream and product events through inference telemetry and observability data, helping Baseten make faster decisions about reliability, performance, adoption and developer experience. RESPONSIBILITIES Partner directly with Product and Engineering: frame the questions that matter, define success criteria, and turn analysis into roadmap, launch, and prioritization decisions. Define how product success is measured: establish metrics across activation, adoption, retention, expansion, reliability and user experience. Support experimentation and launches: design measurement plans, analyze A/B experiments and controlled rollouts, and translate results into product decisions. Diagnose reliability and scaling behavior: join customer signals with request, replica, deployment, and cluster telemetry to find patterns in release bottlenecks, unhealthy replicas, and models without traffic. Define the enterprise customer journey and measure feature adoption along the way Evaluate releases and recovery: measure traffic shifts, evaluate warm-up, drain, probe, and rollback behavior and track MTTR and self-serve incident outcomes. Turn insights into action: analyze customer and cohort behavior, build source-of-truth reporting and self-serve tools, and communicate clear recommendations. REQUIREMENTS 5+ years of experience in product data science, product analytics, or another quantitative role, ideally supporting developer platforms, APIs or B2B products. Deep SQL and Python fluency, with a track record of analyzing large event-level datasets and producing decision-ready work. Strong statistical judgment and practical experimentation experience, including test design, power analysis and knowing when directional evidence is sufficient to act. Hands-on forecasting expertise, including ARIMA, Prophet, or comparable time-series methods, with 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. Preferred Qualifications Experience with AI/ML infrastructure, model serving, GPU systems, or observability for distributed systems. Experience with usage-based pricing, APIs, platform unit economics, capacity planning, and/or enterprise product analytics. Experience with model-serving frameworks and inference engines including vLLM, SGLang and Dynamo. BENEFITS Competitive compensation, including meaningful equity. 100% coverage of medical, dental, and vision insurance for employee and dependents Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) Paid parental leave Fertility and family-building stipend through Carrot Company-facilitated 401(k) Exposure to a variety of ML startups, offering unparalleled learning and networking op