Product Data Scientist

THE ROLE

We're hiring a Product Data Scientist to set up how Baseten uses data to make product decisions. Product is a new function at Baseten, and you'll be one of the people who defines it. You'll work directly with our founders, Product, and Engineering, and alongside GTM, to decide what we measure, how we run experiments, and how the results shape strategy.

This is a foundational, hands-on role. You'll define what success looks like on a technical, usage-based platform, and you'll turn open-ended questions into analyses, forecasts, and experiments. You'll work with everything from clickstream and product events to inference telemetry and observability data, helping Baseten make faster calls on reliability, performance, adoption, and developer experience.

EXAMPLE INITIATIVES

Take a look at these blog posts that show the kinds of systems and data you'll work with:

• How leading platforms ensure observability for LLM inference

• How the Baseten Delivery Network (BDN) makes cold starts fast

• How we built RBAC that scales for the enterprise

RESPONSIBILITIES

• Partner with Product and Engineering to frame the questions that matter, define success criteria, and turn 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 turn the 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 that teams across Baseten can rely on.

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 hands-on experimentation experience, including test design, power analysis, and knowing when directional evidence is enough to act on.

• 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.

NICE TO HAVE

• 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, or enterprise product analytics.

• Experience with model-serving frameworks and inference engines such as vLLM, SGLang, and Dynamo.

BENEFITS

• Competitive compensation, including meaningful equity

• Paid parental leave

• Fertility and family-building stipend through Carrot

• (U.S. only) Company-facilitated 401(k)