Staff Data Scientist

Role Description

Fetch is at a critical inflection point in how data and science inform the company’s most important decisions. With millions of monthly active users, rich item-level purchase data, and increasing investment in AI-driven products like FetchGPT, Fetch has an opportunity to establish a rigorous, scalable measurement and causal reasoning foundation that powers pricing, incentives, growth, marketing investment, and financial planning.

We are seeking a Staff Data Scientist to serve as the company-wide scientific and measurement leader. This role goes beyond traditional analytics or domain ownership. You will:

• Define how Fetch measures value, reasons about causality, and translates evidence into executive decisions.
• Own core measurement frameworks, architect semantic and metric foundations, and set the scientific quality bar across analytics, experimentation, and strategic modeling.
• Within your first year, define Fetch’s MAU × ARPU measurement operating system, establish canonical metrics and semantic standards powering FetchGPT and executive reporting, and deliver strategic models such as marketing mix, elasticity, and incentive sensitivity that directly inform leadership decisions.

Qualifications

• 8+ years of experience in data science, economics, statistics, or applied research, including experience operating at Staff or Principal scope on company and/or org-level problems.
• Deep expertise in causal inference, experimental design, and observational analysis, with demonstrated ownership of high-stakes business decisions informed by causal evidence.
• Experience defining and owning company-level measurement frameworks, canonical metrics, or strategic models used by senior leadership.
• Proven ability to influence and support executive decision-making, including presenting trade-offs, uncertainty, and recommendations that directly impact strategy.
• Exceptional written and verbal communication skills, with the ability to explain complex causal and modeling concepts to non-technical senior audiences.
• Bachelor’s degree in a quantitative field.

Requirements

• Advanced degree in a quantitative discipline.
• Hands-on experience owning and maintaining strategic models such as marketing mix models, elasticity estimates, incentive sensitivity, or long-range forecasts used in executive planning.
• Experience in large-scale consumer products, marketplaces, ad-supported platforms, or incentive-driven systems with complex value trade-offs.
• Experience defining semantic layers, metric governance, or data contracts at scale across multiple teams or functions.
• Demonstrated track record of org-wide scientific leadership without direct people management, including setting standards, reviewing work, and raising the technical bar across teams.

Benefits

• Competitive compensation packages including base, equity, and benefits.