You're a data scientist who moves fast and goes deep. You can spin up an analysis in hours that would take others days; not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You're the person who digs past the top-line number to find the confound, questions whether the metric actually measures what people think it does, and pressure-tests your own work before anyone else sees it. You treat experimentation as a craft, not a checkbox. You've felt the pain of underpowered tests and novelty effects, and you have the judgment to get it right
You use AI agents and tools aggressively to multiply your output - writing code, exploring data, generating hypotheses, but you treat every AI-assisted output as a draft, not a deliverable. You know what good analysis looks like and you won't ship anything that doesn't meet that bar. The result is that you operate at a speed and depth that most DS teams can't match
Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or related field, OR equivalent real-world experience in data roles
5+ years of experience in data science with a focus on product analytics, growth, or user behavior
Strong SQL skills and experience working with large datasets, particularly event-level user behavior data, and designing ETL workflows using dbt
Proficiency in Python and data science libraries (pandas, scikit-learn, statsmodels, etc.)
Experience designing and analyzing A/B tests and experiments, including rigor around sample sizing, power analysis, significance testing, novelty effects, interference between experiments, and causal inference
You leverage AI tools extensively in your own analytical workflow and can demonstrate how they make you more effective, while maintaining high standards for output quality
Experience at a PLG company with a self-serve funnel and freemium or usage-based pricing model
Experience with modern data stack (dbt, BigQuery, Snowflake, Fivetran, etc.) and product analytics platforms (Amplitude, Mixpanel, Segment, etc.)
Experience with causal inference methods (difference-in-differences, synthetic control, propensity score matching)
Experience designing ETL workflows and data pipelines using dbt or similar tools
You've built or contributed to AI-powered analytical tools, automation, or novel measurement approaches
Experience analyzing freemium or usage-based pricing models
Understanding of developer tools, collaborative coding environments, or technical products
Experience working directly embedded with product teams in an agile environment
Familiarity with customer data platforms (CDPs) and event tracking implementation
This is a full-time role that can be held from our Foster City, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday