taskrabbit
Staff Data Scientist
At a Glance
- Location
- San Francisco, California, United States
- Experience
- 7+ years
- Compensation
- ay range for this position is $170,000 - $225,000 . This range is representativ
- Posted
- 2026-07-28T15:55:55-04:00
Key Requirements
Required Skills
Domain Knowledge
- Engineering
Benefits & Perks
with employer-paid health insurance and a 401k match with immediate vesting
Requirements
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; previous experience in a marketplace or fintech company is a plus
Strong and relevant experience with advanced experimentation and statistical modeling; you have past experience with
commerce/risk domain
Expert in SQL, experienced in Python, and familiar with data pipeline tooling (e.g.
Bonus points for experience in productionizing ML models and familiarity with ML Ops.
Compensation & Benefits
At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of base pay + bonus + benefits + perks.
The base pay range for this position is
$170,000 - $225,000
. This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level.
You’ll love working here because:
Taskrabbit is a Hybrid Company.
Responsibilities
As a member of the team, you will help drive our business strategy forward through predictive insights.
We are seeking a highly skilled and motivated Staff Data Scientist to join us, working closely with cross-functional teams from product, finance, engineering, risk and operations to provide data-driven insights and solutions that enhance our products and accelerate growth while minimizing marketplace losses.
Be a strategic thought partner with stakeholders from product, risk, finance, engineering, and operations to define high-impact analytical problems, and solve them using different analytical and statistical approaches.
Proactively perform analytical deep dives to identify strategic growth opportunities in key business levers with a focus on commerce and risk
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
Design, develop, and scale proactive fraud interventions using heuristic and/or machine learning models.