
Senior Data Scientist
Tonal
full-time
Posted on:
Location Type: Hybrid
Location: San Francisco • California • United States
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Salary
💰 $170,000 - $190,000 per year
Job Level
Tech Stack
About the role
- Drive causal and machine learning-based analyses to measure the impact of product features on user behavior, engagement, and business outcomes
- Partner closely with product, analytics engineering, and fellow data scientists
- Build in-house causal inference tools, define KPIs, build production-ready analytical workflows, and deliver high-quality, governed visualizations
- Design, implement, and productionalize statistically rigorous causal analyses
- Develop and maintain causal frameworks that link product interventions to behavioral change, engagement shifts, and business performance
- Validate causal findings through robustness checks, sensitivity analyses, and clear articulation of assumptions and limitations
- Design and deliver high-quality visualizations in Looker and Databricks
Requirements
- 3-5+ years of experience
- Strong statistical experience in causal inference methods like Difference in Difference, propensity score matching, regression discontinuity analysis, and randomized control trials
- Applied experience building and evaluating machine learning models for prediction, segmentation, or uplift in a product or business context
- Ability to develop reproducible, scalable analytical notebooks and workflows that transition effectively from development to production environments
- Experience partnering with product teams to define feature-level KPIs and building robust, well-documented dbt models to expose those metrics across analytics layers
- Strong track record of creating clear, decision-oriented visualizations in tools such as Looker and Databricks that communicate insights unambiguously to cross-functional stakeholders
- Tools and libraries: dbt, databricks, statsmodels, scipy, scikit-learn, causalml, prophet
- Languages: sql, python, r
Benefits
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Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
causal inference methodsDifference in Differencepropensity score matchingregression discontinuity analysisrandomized control trialsmachine learning modelsanalytical notebooksproduction environmentsdbt modelsvisualizations
Soft Skills
collaborationcommunicationdecision-oriented insightsarticulation of assumptionscross-functional teamwork