Data Scientist II

Data Scientist II Department: Data Science Team: Data Scientist Location: San Francisco, United States Type: Full-Time **About the Role** We're looking for a data scientist to join Uber’s **Account Actioning Data Science** team to provide data expertise to ensure that our policies on gaining and maintaining access to the Uber platform are transparent and fair. This will be a highly cross-functional role that will work closely with operations, engineering, product management, and partner data teams. You will build out and own product and operations metrics, provide key insights, conduct deep dive analysis to understand new opportunities and present findings, and work with cross-functional partners on coming up with new policy and product solutions while measuring impact. You will play an influential role in helping drive critical product and policy decisions. **What the Candidate Will Need / Bonus Points** \-\-\-\- What the Candidate Will Do ---- 1. Refine ambiguous questions and generate new hypotheses about the product and business through a deep understanding of the data, our customers, and our business. 2. 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. 3. Collaborate with data scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines. 4. Develop data-driven business insights and work with cross-functional partners to identify opportunities and recommend prioritization of product, growth, and optimization initiatives. \-\-\-\- Basic Qualifications ---- 1. 3+ years proven experience in product analytics or ontological data modeling. 2. M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields. 3. Advanced SQL and Python expertise. 4. Basic understanding of experimental design (such as A/B experiments) and statistical methods. 5. Ability and experience in e