Uber's Account Actioning Data Science team needs data expertise to ensure policies for accessing the Uber platform are transparent and fair, and to drive critical product and policy decisions.
Requirements
- Advanced SQL and Python expertise.
- Basic understanding of experimental design (such as A/B experiments) and statistical methods.
- Ability and experience in extracting insights from data, and summarizing learnings / takeaways.
- Experience with Excel and some dashboarding/data visualization (i.e. Tableau, Mixpanel, Looker, or similar).
- 3+ years proven experience in product analytics or ontological data modeling.
- 4+ years industry experience in consumer facing product analytics.
- Ability to solve complex business problems that cross multiple product/project areas and teams.
Responsibilities
- Refine ambiguous questions and generate new hypotheses about the product and business through a deep understanding of the data, our customers, and our business.
- Define how our teams measure success, by developing Key Performance Indicators and other user/business metrics, in close partnership with Product and other subject areas such as engineering, operations and marketing.
- Collaborate with data scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines.
- Develop data-driven business insights and work with cross-functional partners to identify opportunities and recommend prioritization of product, growth, and optimization initiatives.
- Build out and own operations metrics, provide key insights, conduct deep dive analysis to understand new opportunities and present findings, and work with partners on coming up with new policy and product solutions while measuring impact.
Other
- This will be a highly cross-functional role that will work closely with operations, engineering, product management, and partner data teams.
- Excellent judgment, critical-thinking, and decision-making skills.
- Strong storytelling: distill interesting and hard-to-find insights into a compelling, concise data story.
- Ability to communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds.
- Balance attention to detail with swift execution.
