Policy Applied Scientist - Earnings Policy

Policy Applied Scientist – Earnings Policy

Bachelor’s degree in economics, statistics, math, computer science, or another quantitative field
Familiarity with Python
Demonstrated experience conducting statistical or econometric analysis and synthesizing results into clear, actionable insights
A track record of working independently and conducting research with minimal oversight

Automate the production of fair and accurate earnings statistics; maintain and improve automated reporting pipelines and dashboards for aggregate earnings statistics
Generate research-driven insights on Uber earners’ income, ensuring fairness and accuracy in all public earnings claims
Collaborate cross-functionally with product, legal, policy, operations, engineering, and other teams to translate complex earnings data and risk assessments for a wide range of audiences
Evangelize best practices and advocate for a unified Uber narrative on driver/courier earnings, actively reducing reputational and policy risks

Experience with earnings, labor economics, or policy research, especially involving gig platforms or marketplaces
2+ years’ experience in applied science in a business setting
Exceptional communication skills, with ability to collaborate cross-functionally and translate technical findings for non-technical audiences
Experience maintaining and using large data pipelines and dashboards
Experience with dashboarding tools, SQL, cloud-based data platforms, and AI coding tools
Ability to work independently and proactively identify research questions and data issues relevant to business or policy
Project management skills and experience working in a cross-functional environment with researchers, engineers, and business leaders
Passion for Uber’s mission and for helping shape fair, transparent narratives about driver and courier earnings