**About the Role** The Principal Scientist role supports **Uber Marketplace** by optimizing the engine that manages Driver Pricing and Incentives. This means building and deploying the economic models that balance driver earnings, marketplace efficiency, and rider affordability in real-time across thousands of cities globally. The work involves deep causal inference, machine learning on massive, real-world datasets, and owning the core principles that define a healthy, liquid marketplace where you **move the real world** at enormous scale. Success in this role requires not only generational technical depth but also the ability to drive high-stakes alignment on ambiguous problems with Director and VP-level leaders in Product, Engineering, and Operations. You will navigate constant trade-offs between short-term growth and long-term marketplace sustainability, demanding a deep **trip obsessed** mindset to simplify immense complexity. If you are ready to set the technical direction for one of Uber's most critical and high-impact product areas, this is where you will grow with the challenge. **What You’ll Do** - **Define** the long-term science roadmap for Driver Pricing, matching, and Incentives, translating ambiguous business problems into rigorous, implementable economic and machine learning solutions that drive step-change improvements. - **Design** and lead the implementation of complex causal inference and large-scale experimentation (A/B testing) frameworks to measure the true, long-term impact of pricing and incentive policy changes on both driver behavior and overall marketplace health. - **Drive** excellence and rigor in science methodologies, leveraging techniques such as machine learning, experimentation, causal inference, time series analysis, and natural language processing to address complex marketplace challenges. - **Build** critical, cross-functional alignment with senior Product, Engineering, and Operations leaders, using deep data-driven narratives to advocate for, influence the roadmap of, and secure resources for multi-quarter, multi-team initiatives. - **Act** as the organization's technical authority on marketplace dynamics, providing authoritative guidance on model architecture, elevating the science bar across the domain, and mentoring Staff and Senior Data Scientists. - **Unblock** critical, large-scale system bottlenecks by investigating and solving data quality, model drift, and real-time performance issues, often requiring deep dives into engineering architecture and production systems. **How you’ll spend your time** - 40% Strategic Research & Model Design (Deep work, defining technical direction) - 30% Cross-functional Leadership & Alignment (Stakeholder reviews, presenting and influencing) - 20% Mentorship & Technical Review (Design reviews, guiding team members) - 10% Production Debugging & Incident Response (Unblocking major, high-stakes issues) **What You’ll Need** - **15+ years of demonstrable experience** as an Individual Contributor (IC) in a Data Science, Applied Science, or Quantitative Research role at a high-scale technology company. - **Ph.D. degree** in a quantitative field such as Computer Science, Operation Research, Math, Statistics, or Economics; OR **18+ years of relevant experience** in lieu of a Ph.D. - **8+ years of experience** directly designing, deploying, and owning real-time machine learning or economic policy systems that govern multi-sided marketplaces or high-volume transactional platforms. - **Demonstrated proficiency** in advanced causal inference, large-scale experimentation design (A/B testing), and model development using Python, R, and advanced SQL. **Bonus Points If** - Proven ability to mentor senior and staff-level Scientists, raising the overall technical capability and **systems thinking** rigor across multiple teams, even without direct reporting lines. - Deep practical experience navigating technical debt and legacy systems while driving simultaneous, net-new development in a fast-paced environment, reflecting high **adaptability**. - Exceptional track record of influencing executive-level product and business leaders through clear, concise, and non-jargon-heavy storytelling, demonstrating strong **person orientation/interpersonal influence**. - Experience with advanced economic modeling, optimization techniques (e.g., matching, routing), or other Operations Research techniques applied to real-world, high-stakes environments. **About the Team** The [Uber Marketplace](https://www.uber.com/us/en/marketplace/?uclick_id=2865c29d-7207-4c2d-80a5-29617f789889) is designed to move riders & drivers efficiently from where they are to where they want to go. Every dollar that is transacted in the Uber Marketplace (driver forecasting, dynamic pricing fares, matching driver/rider pricing, and overall marketplace health) is informed and influenced by data – and our Data Science team understands, analyzes, and helps design the algorithms that enable millions of earners and consumers to ride, deliver, eat, and move daily. Uber operates in a constantly-evolving and competitive environment, across a diverse set of markets and product categories. Assessing the success or failure of a product or investment strategy depends on deeply understanding this context and quantifying the impact with thoughtfully-defined success metrics. Doing this - and doing it well - at Uber’s global scale is an interesting and complex problem with meaningful impact on our P&L. The Marketplace Data Science team applies their expertise in statistical modeling, machine learning, economics, data analysis, and business strategy to build scalable data platforms, generate actionable insights, and drive our algorithm and product development decisions. For San Francisco, CA-based roles: The base salary range for this role is USD$270,000 per year - USD$300,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$270,000 per year - USD$300,000 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](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.