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We are looking for an Applied Scientist to join the Safety Science Team. At Uber, Stand for Safety is one of our core values. In this role, you’ll have the amazing opportunity to help contribute to making the Uber platform as safe as possible by leveraging analytics and machine learning. You’ll have a chance to work with a highly cross-functional team, including product management, engineering, and operations to deliver impact. This will include owning the end-to-end applied science workflow on high visibility projects such as problem scoping, deep-dive analysis to size up opportunities and to surface insights, developing models, and driving experimentation. You’ll be able to present findings to partners and leadership.
Job Responsibility:
Design, develop, and deliver sophisticated applied ML models from ideation to production, ensuring robustness and measurable safety impact
Conduct complex, rigorous deep-dive analyses and causal inference to uncover root causes and identify high-leverage safety opportunities
Own the design, analysis, and interpretation of A/B experiments to rigorously evaluate product and policy changes before platform rollout
Requirements:
Ph.D., M.S. or Bachelor's degree in Computer Science, Statistics, Mathematics, Operations Research, or a related quantitative field, OR equivalent experience
3+ years (with Ph.D.) or 5+ years (with M.S. or B.S.) of industry experience building and deploying machine learning models or conducting high-impact applied data science in a large-scale production environment
Expert proficiency in core machine learning principles, including classification, regression, time series analysis, and causal inference
High proficiency in at least one programming language (e.g., Python or Scala) and expertise in data manipulation using SQL
Nice to have:
Ph.D. in Computer Science, Statistics, Mathematics, Operations Research, Economics
Professional experience in safety, risk, or fraud
Hands-on experience with LLM including high scale production implementations