Product Data Scientist

Jobtailor; California (MO); On-site; USD 150,000 - 210,000; Full time

Job summary

Baseten is seeking a Product Data Scientist to partner with Product and Engineering to frame questions and turn analysis into roadmap decisions for a leading AI inference platform.

You will define product-success metrics across activation, adoption, retention, expansion, reliability, and user experience; design measurement plans; and translate results into actionable product decisions that drive enterprise outcomes.

Qualifications

• 5+ years of experience in product data science, product analytics, or another quantitative role.
• Fluent in SQL and Python.
• Experience analyzing large event-level datasets and producing decision-ready work.
• Strong statistical judgment and practical experimentation experience, including test design and power analysis.
• Hands-on forecasting expertise, including ARIMA, Prophet, or comparable time-series methods.
• Experience 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.
• Experience with AI/ML infrastructure, model serving, GPU systems, or observability for distributed systems preferred.
• Experience with usage-based pricing, APIs, platform unit economics, capacity planning, and/or enterprise product analytics preferred.
• Experience with model-serving frameworks and inference engines including vLLM, SGLang, and Dynamo preferred.

Responsibilities

• Partner directly with Product and Engineering, alongside GTM, to frame important questions, 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, analyze A/B experiments and controlled rollouts, and translate results into product decisions
• Diagnose reliability and scaling behavior by joining customer signals with request, replica, deployment, and cluster telemetry
• Define the enterprise customer journey and measure feature adoption
• Evaluate releases and recovery, including traffic shifts, warm-up, drain, probe, rollback behavior, MTTR, and self-serve incident outcomes
• Analyze customer and cohort behavior, build source-of-truth reporting and self-serve tools, and communicate recommendations
• Work with Product, Engineering, and GTM to establish data-driven product decision-making at Baseten, an AI inference platform

Skills

Product Data Science

SQL Fluency

Python Proficiency

A/B Testing

Time-Series Forecasting

Tools

dbt

Sigma

Hex

BI Tools

Job description

• Partner directly with Product and Engineering, alongside GTM, to frame important questions, 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, analyze A/B experiments and controlled rollouts, and translate results into product decisions
• Diagnose reliability and scaling behavior by joining customer signals with request, replica, deployment, and cluster telemetry
• Define the enterprise customer journey and measure feature adoption
• Evaluate releases and recovery, including traffic shifts, warm-up, drain, probe, rollback behavior, MTTR, and self-serve incident outcomes
• Analyze customer and cohort behavior, build source-of-truth reporting and self-serve tools, and communicate recommendations
• Work with Product, Engineering, and GTM to establish data-driven product decision-making at Baseten, an AI inference platform

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
• Track record of analyzing large event-level datasets and producing decision-ready work
• Strong statistical judgment and practical experimentation experience, including test design and power analysis
• Hands-on forecasting expertise, including ARIMA, Prophet, or comparable time-series methods
• Experience 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
• Experience with AI/ML infrastructure, model serving, GPU systems, or observability for distributed systems preferred
• Experience with usage-based pricing, APIs, platform unit economics, capacity planning, and/or enterprise product analytics preferred
• Experience with model-serving frameworks and inference engines including vLLM, SGLang, and Dynamo preferred
• Ability to work onsite Tuesday–Thursday in the San Francisco or New York office
• Unrestricted work authorization in the United States

Core Competencies

Demonstrates expertise in product data science and analytics, with a strong focus on SQL and Python for analyzing large datasets and driving data-informed product decisions. Proficient in designing measurement plans, A/B testing, and developing data architectures to support enterprise-level product analytics.

Highest-signal resume keywords

• Product Data Science
• SQL Fluency
• Python Proficiency
• Statistical Judgment
• A/B Testing Experience

Hard Skills

• Data Analysis
• Statistical Experimentation
• Forecasting Expertise
• Time-Series Methods
• Backtesting
• Error Analysis
• Medallion Data Architecture
• Data Documentation
• Model Serving Frameworks
• Usage-Based Pricing

Industry Keywords

• B2B Products
• APIs
• Developer Platforms
• Enterprise Product Analytics
• Capacity Planning

Tools & Technologies

• BI Tools
• Dbt
• Sigma
• Hex
• AI/ML Infrastructure
• GPU Systems
• Observability Tools