Senior Data Scientist
$161,300–$274,200 year
On-siteMountain View Santa Clara County, California, United States
Job Summary
Partner with executive, product, and engineering teams to define and govern critical product metrics, applying rigorous statistical and machine learning techniques to identify levers driving core outcomes. Analyze engineering system performance by isolating signal from noise, then lead the design and ownership of scalable analytical systems and AI-native integrations that automate established analyses and empower self-serve insights. Drive the development of DS workflows, provide technical mentorship to junior data scientists, and establish best practices for data modeling and pipeline design. This role requires an M.S. or Ph.D. in a quantitative field with 5+ years of experience in enterprise analytics, LLM evaluation, and distributed systems, with a base pay range of $161,300 - $274,200 plus equity and benefits.
Required Qualifications
- M.S. or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field
- 5+ years of progressive experience building and deploying production analytics or ML solutions for enterprise software products
- Demonstrated expertise in LLM evaluation methodology, including dataset curation, benchmarking, and regression detection for AI/LLM systems
- Proven experience architecting scalable data pipelines using distributed systems (e.g., PySpark/Spark SQL), orchestration frameworks (e.g., Airflow), and cloud platforms (e.g., AWS EMR, S3, Snowflake or equivalent)
- Proficiency in Python and SQL
- Demonstrated ability to lead technical workstreams and drive cross-functional alignment
- Experience providing technical leadership and mentoring to data scientists or engineers
- Experience building evaluation pipelines or harnesses for agentic or LLM-powered systems
- Experience with conversational analytics, NLP, or AI-assisted data exploration tooling
- Prior work on self-serve analytics platforms or customer-facing data products at enterprise scale
- Experience using modern AI productivity tooling (e.g., Claude, Cursor, Codex) within an enterprise SDLC
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