Senior Scientist, Uber For Business

Job Description

About the Role Uber for Business (U4B) brings the utility and convenience of Uber to organizations. We build innovative products on top of Ubers rides and delivery platforms, including Uber Health and Vouchers, and are a key part of the companys next phase of growth. The U4B Science teams mission is to understand and improve U4B products through data insights. We own complex projects from end-to-end, including analysis and experimentation, and we are a full-stack team covering everything from strategic product analysis to data foundations. ---- What You Will Do ---- Refine ambiguous questions and generate new hypotheses about the product through a deep understanding of the data, our customers, and our business Design experiments and interpret the results to draw detailed and impactful conclusions. Define how our teams measure success, by developing Key Performance Indicators and other users/business metrics, in close partnership with Product and Engineering Develop data-driven business insights and work with cross-functional partners to find opportunities and recommend prioritisation of product, growth, and optimisation initiatives. Collaborate with applied scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines. ---- What You Will Need ---- Undergraduate and/or graduate degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative fields. 5+ years experience as a Product Analyst, Sr. Data Analyst, or other types of data analysis-focused functions Excellent understanding of statistical principles backed by an academic foundation Experience with SQL and either Python or R for data analysis Proven track record to wrangle large datasets, extract insights from data, and summarise learnings/takeaways. Experience with dashboarding and data visualisation (i.e. Tableau, Mixpanel, Looker, or similar) ---- Preferred Qualifications ---- Significant experience in setting up and evaluating complex experiments, especially in marketplaces Experience in modeling or causal inference