Senior Data Scientist

🕒 January 21

🏢🏡 San Francisco – Hybrid

💵 $170k - $190k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Tonal

WebsiteLinkedInAll Job Openings

501 - 1000 employees

👥 B2C

🔧 Hardware

B2C • Fitness • Hardware

Tonal is a cutting-edge home gym system that combines technology and exercise science to offer a personalized and efficient workout experience. It provides real-time resistance adjustments and data-driven coaching to help users maximize their fitness routine. With expert coaching, personalized tracking, and a variety of energizing workouts, Tonal aims to promote strength training and overall fitness from the convenience of home. This smart gym system uses AI to deliver insights and tailor workouts, ensuring users are always challenged and motivated to improve their physical health.

📋 Description

• 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

• Offers Equity