Senior Data Scientist

About the Role

The Uber Maps team is at the forefront of advancing Uber’s geospatial technologies, crucial for driving the efficiency and reliability of Uber services. We work across a diverse array of problem domains, including: curating and improving precision of location (i.e. ‘Places’) data, developing cutting-edge location search algorithms for each Rides pickup/dropoff and Eats delivery, building base maps and correcting map errors, as well as optimizing routes and travel time predictions, and more. These pivotal technologies are the backbone of every decision made in our marketplace, influencing dispatch and pricing strategies directly.

If you're passionate about driving innovation and have relevant experiences in tech or marketplace settings, we sincerely welcome you to join our team and shape the future of Uber's geospatial technologies together.

You can learn more about our team through:

• Fixing Map Errors with GPS Data
• What’s my ETA? A Billion $ question
• Rethinking GPS: Engineering Next-Gen Location at Uber
• Enhancing the Quality of Uber’s Maps with Metrics Computation

What You'll Do

We are looking for data scientists who thrive in solving complex, large-scale challenges to advance Uber’s geospatial capabilities. Our ideal candidates are professionals with substantial hands-on experience from the tech industry, with solid knowledge in machine learning, statistics, experimental design, and/or operations research. Experiences with solving multi-sided marketplace problems is a plus.

In this role, you will apply your expertise to a variety of critical tasks, including

• Developing models to address ambiguous challenges using statistical, machine learning, and optimization techniques.
• Collaborating closely with product development teams to prototype and productionize models, enhance data observability and metrics, and conduct experiments.
• Driving team roadmap and vision through identifying opportunities and building data-driven solutions.
• Delivering insightful presentations on models, solutions, and data analytics findings to stakeholders and leadership.

Basic Qualifications

• Ph.D., M.S., or Bachelors degree in Statistics, Economics, Operations Research, or other quantitative fields.
• Minimum 3 years of industry experience as a Data Scientist or equivalent.
• Experience in experimental design and analysis, exploratory data analysis and statistical analysis.
• Experience with dashboard/data visualization toolings.
• Ability to use Python to work efficiently at scale with large data sets.
• Proficiency in SQL.

Preferred Qualifications

• Experience working in a marketplace environment within the technology industry
• Ability to use Python/R for exploratory data analysis and ML modeling development.
• Experience in algorithm prototyping and development.
• Experience in partnering with cross-functional stakeholders to execute decisions.
• Proficiency in programming languages including Java and Go.

For San Francisco, CA-based roles: The base salary range for this role is USD$165,000 per year - USD$183,000 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.

Uber is proud to be an Equal Opportunity/Affirmative Action 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.