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$161,000 per year - USD$179,000 per year.
You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link [https://jobs.uber.com/en/benefits](https://jobs.uber.com/en/benefits).
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.
