**About the Team** 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. **About the Role** 1. Modeling & Production: Design, develop, and deliver sophisticated applied ML models from ideation to production, ensuring robustness and measurable safety impact. 2. Deep-Dive & Insights: Conduct complex, rigorous deep-dive analyses and causal inference to uncover root causes and identify high-leverage safety opportunities. 3. Experimentation: Own the design, analysis, and interpretation of A/B experiments to rigorously evaluate product and policy changes before platform rollout. **What the Candidate Will Need** \-\-\-\- What the Candidate Will Do ---- 1. Modeling & Production: Design, develop, and deliver sophisticated applied ML models from ideation to production, ensuring robustness and measurable safety impact. 2. Deep-Dive & Insights: Conduct complex, rigorous deep-dive analyses and causal inference to uncover root causes and identify high-leverage safety opportunities. 3. Experimentation: Own the design, analysis, and interpretation of A/B experiments to rigorously evaluate product and policy changes before platform rollout. 4. Cross-Functional Influence: Partner closely with Product Managers, Engineers, and Policy teams to translate data-driven insights into critical product features and company-wide safety policies. \-\-\-\- Basic Qualifications ---- 1. Education: Ph.D., M.S. or Bachelor's degree in Computer Science, Statistics, Mathematics, Operations Research, or a related quantitative field, OR equivalent experience. 2. 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. 3. Technical Depth: Expert proficiency in core machine learning principles, including classification, regression, time series analysis, and causal inference. 4. Programming: High proficiency in at least one programming language (e.g., Python or Scala) and expertise in data manipulation using SQL. \-\-\-\- Preferred Qualifications ---- 1. Ph.D. in Computer Science, Statistics, Mathematics, Operations Research, Economics 2. Professional experience in safety, risk, or fraud 3. Hands-on experience with LLM including high scale production implementations For San Francisco, CA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits). Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A). Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.