Staff Data Scientist

About Taskrabbit

Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love.

Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories.

Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed!

• We are currently unable to provide visa sponsorship for this position (including H-1B, OPT, F1, CPT or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future.
• This role is hybrid requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St, San Francisco, CA).

Data Science plays a crucial role in driving impact  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. 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 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. These efforts will be focused on enhancing financial performance by mitigating issues such as chargebacks, fraud, transaction declines, and refunds.
• Foster a data-driven culture within the organization by advocating for best practices in data analysis and interpretation.

• 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; 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 fraud/risk models in a marketplace/fintech context
• 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 product ionizing 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.

At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of…