SlipstreamJobsFresh Startup & VC-Backed Jobs

Staff Data Scientist

Taskrabbit - San Francisco, CA, United States - Hybrid - posted 2026-02-28

Apply on the company site

SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.

Salary: USD 170,000 - 225,000 / annual

Taskrabbit is a marketplace platform connecting people with Taskers for everyday home services like furniture assembly, handyman work, and moving help. The company is owned by IKEA and operates across the US and EU with a hybrid workforce. As a Staff Data Scientist, you will serve as a strategic thought partner across product, risk, finance, engineering, and operations teams. Your primary focus will be driving business strategy through predictive insights and data-driven solutions that enhance products, accelerate growth, and minimize marketplace losses. Key responsibilities include: - Defining and solving high-impact analytical problems using advanced statistical and analytical approaches, presenting actionable insights to executive stakeholders - Conducting strategic analytical deep dives to identify growth opportunities in commerce and risk domains - Collaborating with stakeholders to define success metrics, conduct advanced experimentation, and apply causal inference to optimize product features and user experiences - Designing, developing, and scaling proactive fraud interventions using heuristic and machine learning models to mitigate chargebacks, fraud, transaction declines, and refunds - Fostering a data-driven culture by advocating for best practices in data analysis and interpretation You will need a BS, MS, or PhD in a quantitative field (Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research, or related). Minimum 7 years of industry data science experience is required, with preference for marketplace or fintech background. You must have strong experience with advanced experimentation, statistical modeling, and fraud/risk models in marketplace or fintech contexts. Expert SQL proficiency, Python experience, and familiarity with data pipeline tools (dbt) and git are essential. Experience productionizing ML models and MLOps knowledge is a bonus. The role requires excellent analytical and problem-solving skills, strong business acumen in commerce/risk domains, and the ability to communicate complex findings clearly to executives. You should be a self-starter capable of driving projects end-to-end with demonstrated business impact. This is a hybrid role requiring 2 days in office at the San Francisco hub (130 Sutter St) every Tuesday and Wednesday. Visa sponsorship is not available; candidates must be legally authorized to work in the US.

Similar roles