Applied Scientist - Legal Data and Economics

Applied Scientist - Legal Data and Economics Department: Data Science Team: Data Scientist Location: San Francisco, United States Type: Full-Time **About the Role** Applied science can drastically advance and accelerate modern legal work. Uber’s legal applied science team uses applied science to partner with legal, compliance, and security professionals, harnessing the power of tools ranging from SQL queries to genAI. They partner with the Legal team globally and use their understanding of Uber data and the Uber platform to answer legal questions and inform legal and factual arguments with data. As part of this work, they analyze large datasets, create data pipelines, and build statistical models. **What the Candidate Will Need / Bonus Points** \-\-\-\- What the Candidate Will Do ---- 1. Build a deep, nuanced understanding of Uber’s large and unique data as well as its platform and communicate this understanding to lawyers, regulators, and other stakeholders 2. Propose, design, and execute data analyses, data pipelines, and statistical models to inform, enrich, and advance the work of our Legal Team and other teams across the company 3. Evaluate and quantify risk using a variety of quantitative methods for the Legal Team 4. Work in an inclusive and diverse team of data scientists who will support your development as a data scientist and who, in turn, you will influence and shape \-\-\-\- Basic Qualifications ---- 1. 4+ Years professional experience and demonstrated interest in quantitative analysis of legal, economic, or policy issues 2. Experience using and picking up data science tools to query (e.g., SQL) and analyze (e.g., Python, R) data at scale 3. Ability to collaborate and communicate well: building and managing relationships with clients, communicating with non-technical audiences, and collaborating with cross-functional partners 4. Ability to own and drive projects independently: balancing excellence and attention to detail with the need to prioritize work and deliver within tight deadlines \-\-\-\- Preferred Qualifications ---- 1. Advanced degree in relevant field (economics, statistics, po