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# Data Science

- **Company:** TaskRabbit
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Python (Programming Language), Machine Learning, SQL Databases, Git, Information Technology, Machine Learning Operations, Data Pipelines
- **Published:** September 19, 2026
- **Apply:** https://startup.jobs/staff-data-scientist-taskrabbit-10116987

## About the Role

* BS, MS or Ph.D. in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research, or related field).
 * A minimum of 7 years industry experience in data science
 * Strong and relevant experience with advanced experimentation and statistical modeling
 * Excellent analytical and problem-solving skills.
 * Excellent business acumen and strategic thinking skills, especially in a commerce/risk domain
 * Expert in SQL, experienced in Python, and familiar with data pipeline tooling (e.g. dbt) and git. Bonus points for experience in productionizing ML models and familiarity with ML Ops.
 * A self-starter with the ability to work independently and drive your own projects end-to-end with a track record of landing strong business impact
 * Ability to communicate complex data findings in a clear and concise manner to an executive audience.

## Description

Data Science plays a crucial role in driving impact at Taskrabbit. We are seeking a highly skilled and motivated Staff Data Scientist to join us, working closely with cross-functional teams from Product teams and occasionally Commercial Operations to provide data-driven insights and solutions that enhance our products and accelerate growth while minimizing marketplace losses.

What you will work on

 * Be a strategic thought partner with stakeholders in Product and occasionally Commercial Operations to define high-impact analytical problems, and solve them using different analytical and statistical approaches. Present actionable insights in a clear and compelling manner.
Proactively perform analytical deep dives to identify strategic growth opportunities in key business levers with a focus on Product
Collaborate with stakeholders to define and measure success metrics for new features and products, conduct advanced experimentation and causal inference to optimize product features and user experiences
Lead central Data Science initiatives, e.g. experimentation system, building data agents, influencing eventing systems, etc.
Foster a data-driven culture within the organization by advocating for best practices in data analysis and interpretation.


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