Baseten
Product Data Scientist
San Francisco · Senior
Sponsorship not specifiedDetected 10 days ago
PythonSQLMachine LearningSparkdbtData ScienceLLMsA/B TestingForecastingResearch
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About the role
- How leading platforms ensure observability for LLM inference https://www.baseten.co/blog/how-leading-platforms-ensure-observability-for-llm-inference/
- How the Baseten Delivery Network (BDN) makes cold starts fast https://www.baseten.co/blog/how-the-baseten-delivery-network-bdn-makes-cold-starts-fast/
- How we built RBAC that scales for the enterprise https://www.baseten.co/blog/rbac-from-the-ground-up-solving-for-autonomy-vs-control/
Responsibilities
- Partner with Product and Engineering to frame the questions that matter, define success criteria, and turn analysis into roadmap, launch, and prioritization decisions.
- Design measurement plans for launches, analyze A/B experiments and controlled rollouts, and turn the results into product decisions.
- Build source-of-truth reporting and self-serve tools that teams across Baseten can rely on.
- We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital.
- Join us and help build the platform engineers turn to ship AI products.
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.
- 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.
Compensation
- Competitive compensation, including meaningful equity
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
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
- 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.
- 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.
Company info
- At Baseten, we are committed to fostering a diverse and inclusive workplace.
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