About the Role

The Road Safety team is dedicated to safeguarding the Uber platform by applying cutting-edge data science and machine learning to proactively mitigate and make rare safety events even rarer. As a Staff Applied Scientist, you will be responsible for setting the technical direction to develop and deploy high-impact, production-ready machine learning models, conducting rigorous deep-dive analyses to inform strategy, and designing/evaluating complex experiments (A/B testing). Your work will play an influential and highly visible role in driving critical product, policy, and engineering decisions that ensure our platform is as safe as possible for all users globally.

What the Candidate Will Do

• Technical Leadership & Strategy: Define the strategic roadmap and set the technical direction for developing and deploying large-scale, high-performance machine learning systems focused on proactive safety prediction and mitigation.
• Modeling & Production: Design, develop, and deliver sophisticated applied ML models from ideation to production, ensuring robustness and measurable safety impact.
• Deep-Dive & Insights: Conduct complex, rigorous deep-dive analyses and causal inference to uncover root causes and identify high-leverage safety opportunities.
• Experimentation: Own the design, analysis, and interpretation of A/B experiments to rigorously evaluate product and policy changes before platform rollout.
• 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

• Education: Ph.D. in Computer Science, Statistics, Mathematics, Operations Research, or a related quantitative field, OR equivalent experience.
• Experience: 8+ years (with Ph.D.) or 10+ 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.
• Technical Depth: Expert proficiency in core machine learning principles, including classification, regression, time series analysis, and causal inference.
• Programming: High proficiency in at least one programming language (e.g., Python or Scala) and expertise in data manipulation using SQL.
• System Scale: Demonstrated experience designing and delivering end-to-end ML solutions that operate at significant scale (handling large datasets and high-velocity systems).
• Strategic Impact: Proven track record of influencing product or policy decisions using rigorous analysis, experimentation (A/B testing), and clear communication of complex technical results to non-technical stakeholders.

Preferred Qualifications

• Insurance/Actuarial Fundamentals: Applied knowledge of core insurance concepts such as:

• Risk Modeling: Understanding of concepts like frequency, severity, and loss development .

• Loss Cost & Pricing: Familiarity with how safety events translate into financial loss (expected claims/payouts) and the inputs for risk-based pricing or economic valuation of safety interventions.

• Telematics: Experience leveraging granular sensor or telematics data to model driver behavior and assess accident probability.

• For New York, NY-based roles: The base salary range for this role is USD**$212,000 per year**

• USD**$235,500 per year**.

• For San Francisco, CA-based roles: The base salary range for this role is USD**$212,000 per year**

• USD**$235,500 per year**.

• For Seattle, WA-based roles: The base salary range for this role is USD**$212,000 per year**

• USD**$235,500 per year**.

• For Sunnyvale, CA-based roles: The base salary range for this role is USD**$212,000 per year**

• USD**$235,500 per year**.
  For all US locations, 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.
  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.
  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.