Data Scientist
The Data Scientist will serve as an embedded analytical partner to product and business leaders, owning experimentation, causal inference, predictive modeling, and metric design. The role requires 5+ years of data science experience, expert SQL and Python, strong statistical foundations, and the ability to influence strategic decisions.
About the job
Responsibilities
- Own causal inference and experimentation.
- Design and analyze experiments, and build incrementality measurement where clean A/B tests are not possible, including propensity-score matching to estimate feature and go-to-market channel lift.
- Define how the business is measured.
- Shape metric trees connecting team-level metrics to company outcomes.
- Establish success criteria for product launches.
- Build frameworks for sizing and forecasting impact.
- Build predictive models that focus teams on the most important priorities.
- Root-cause anomalies and investigate nuanced behavioral questions.
- Create analysis frameworks for questions that do not fit existing patterns.
- Teach the organization what to focus on and what to ignore through data.
- Partner directly with leaders, turning ambiguous strategic questions into rigorous, decision-ready analysis.
Requirements
- 5+ years of experience in data science, with demonstrated ownership of experimentation, causal inference, or predictive modeling.
- Strong product and business sense, with a track record of influencing product and business decisions.
- Strong statistical and experimentation foundations, including experiment design, effect estimation, exploratory analysis, and evaluating result reliability.
- Expert SQL and Python skills.
- Experience using AI tools such as Claude Code, Cursor, or similar tools to accelerate analytical work.
- Clear communication skills and the ability to influence senior stakeholders.
Nice to Have
- Experience with Snowflake, GitHub, dbt, Hex, Sigma, or Dagster.
- Experience in product-led growth or B2B SaaS, especially usage-based pricing.
- Experience partnering with ML engineers to productionize models.
Compensation and Benefits
- Hybrid work arrangement.
- Employees can work for free with world-class coaches specializing in creativity, management, and more.
Skills
SQL, Python, Causal Inference, Experiment Design, Predictive Modeling, Statistical Analysis, A/B Testing, Propensity Score Matching, Snowflake, GitHub, dbt, Hex, Sigma, Dagster
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