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Salary: USD 170,000 - 225,000 / annual
Taskrabbit is a marketplace platform connecting people with Taskers for everyday home services including furniture assembly, handyman work, moving help, and more. The company is owned by IKEA and operates as a hybrid organization with employees across the US and EU.
In this Staff Data Scientist role, you will be a strategic thought partner with Product and Commercial Operations teams, driving high-impact analytical work that enhances products and accelerates growth while minimizing marketplace losses. You will define and solve complex analytical problems using advanced statistical and analytical approaches, presenting actionable insights to executive audiences.
Key responsibilities include:
- Serving as a strategic advisor to Product and Commercial Operations stakeholders to identify and solve high-impact analytical problems
- Conducting proactive analytical deep dives to identify strategic growth opportunities in key business levers, with focus on Product
- Collaborating with stakeholders to define success metrics for new features and products, conducting advanced experimentation and causal inference to optimize product experiences
- Leading central Data Science initiatives such as experimentation systems, building data agents, and influencing eventing systems
- Fostering a data-driven culture by advocating for best practices in data analysis and interpretation
The role is hybrid, requiring 2 days in office at the San Francisco hub (130 Sutter St) every Tuesday and Wednesday.
Requirements:
- BS, MS, or Ph.D. in a quantitative field (Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research, or related field)
- Minimum 7 years of 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 commerce/risk domains
- Expert-level SQL proficiency, experienced in Python, and familiar with data pipeline tooling (e.g., dbt) and git
- Bonus: experience productionizing ML models and familiarity with ML Ops
- Self-starter capable of working independently and driving projects end-to-end with a track record of strong business impact
- Ability to communicate complex data findings clearly and concisely to executive audiences
- Must be legally authorized to work in the United States without employer sponsorship (no visa sponsorship available)
