Product Data Scientist

Posted 2 Days Ago
2 Locations
Hybrid
185K-240K Annually
Senior level
Software
Inference will be the largest market ever created.
The Role
The Product Data Scientist will establish data-driven product decision-making at Baseten. Responsibilities include defining product metrics, designing measurement plans, analyzing experiments and customer behavior, forecasting, evaluating platform reliability and releases, and building trusted reporting tools. The role partners closely with Product, Engineering, founders, and GTM to guide roadmap and prioritization decisions across a technical, usage-based AI platform.
Summary Generated by Built In

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 ship AI products.

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

  • (U.S. only) 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

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

  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Skills Required

  • 5+ years of experience in product data science, product analytics, or another quantitative role
  • Experience supporting developer platforms, APIs, or B2B products
  • Deep SQL and Python fluency
  • Experience analyzing large event-level datasets and producing decision-ready work
  • Strong statistical judgment and hands-on experimentation experience
  • Experience with test design and power analysis
  • Experience determining when directional evidence is sufficient for action
  • Hands-on forecasting experience with ARIMA, Prophet, or comparable time-series methods
  • Experience with disciplined backtesting, error analysis, and scenario planning
  • Experience designing medallion data architectures with raw, conformed, and business-ready models
  • Experience with data testing, documentation, and lineage
  • Familiarity with dbt, semantic layers, and data ontology
  • Familiarity with BI tools such as Sigma or Hex
  • Experience with AI/ML infrastructure, model serving, GPU systems, or distributed-systems observability
  • Experience with usage-based pricing, APIs, platform unit economics, capacity planning, or enterprise product analytics
  • Experience with model-serving frameworks or inference engines such as vLLM, SGLang, and Dynamo

Baseten Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Baseten and has not been reviewed or approved by Baseten.

  • Fair & Transparent Compensation — Feedback suggests pay targets the top of market with explicit ranges in postings and a stated aim to provide 90th percentile salaries with equity. Role descriptions emphasize competitive, experience-based pay bands and meaningful stock grants.
  • Healthcare Strength — Healthcare is described as fully covered for medical, dental, and vision for employees and their families, reducing out-of-pocket costs. This comprehensive coverage is consistently highlighted alongside other core benefits.
  • Leave & Time Off Breadth — Time off policies include unlimited PTO with a minimum expectation of at least four weeks, 16 paid company holidays, and a company-wide winter break. These elements indicate substantial protected time away from work.

Baseten Insights

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The Company
HQ: San Francisco, CA
350 Employees
Year Founded: 2019

What We Do

AI’s future won’t be a few massive models built by a handful of labs. It’ll be millions of specialized models embedded into every product, workflow, and experience by the people closest to the customer. The foundation of that future is inference. Inference determines the performance, reliability, latency, and economics of every AI product. For AI to scale globally, it must be as reliable, fast, cost-effective, and high-quality as possible. That’s why Baseten exists. Companies like Abridge, Cursor, Lovable, Notion, and OpenEvidence depend on Baseten to power mission-critical AI workloads in production.

Why Work With Us

We’re an interdisciplinary team of researchers, engineers, and operators building the Inference Cloud our AI future demands. We’re running at a hard systems problem that requires first-principles thinking across the entire stack. The bar is high. We work hard, move fast, and care deeply about quality.

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