About the Role

Uber Eats has grown into a global marketplace that Eaters and merchants alike rely on to meet their needs. For Eaters, offers and affordability are two of the most important aspects of the platform that drive both value and delight.
As a Sr. Scientist on Offers and Affordability, you will guide how offers and affordable selection are integrated and displayed on Uber Eats to Eaters. You will be a thought partner for a wide breadth of topics ranging from the optimization of existing surfaces to the ideation and implementation of entirely new bets. This is a highly visible, cross-functional role where you'll combine technical expertise with product intuition to shape key pillars of Uber's strategy.
We're seeking an experienced scientist with strong analytical acumen, technical depth, and a passion for solving complex, real-world problems.
What the Candidate Will Need / Bonus Points What You'll Do

1. Lead analytical initiatives in collaboration with cross-functional teams across disciplines such as product, engineering, and marketing to drive strategy and priorities.
2. Refine ambiguous questions and generate new hypotheses about the product through a deep understanding of data, our customers, and our business.
3. Design, implement, and analyze experiments and causal inference studies.
4. Define how our teams measure success, by developing metrics, in close partnership with cross functional partners.
5. Communicate findings clearly to technical and non-technical leaders to influence decisions and product direction.

Basic Qualifications:

1. A degree in Statistics, Economics, Operations Research, or a related quantitative field.
2. Mininum 4 years of relevant industry experience as a Data Scientist, Applied Scientist, or equivalent (2+ years if holding a Ph.D.).
3. Experience in experimental design and analysis.
4. Strong analytical skills, with experience extracting user behavior insights from large datasets.
5. Solid theoretical and applied causal inference skills, experience applying them in a practical industry setting.
6. Proficiency with Python and SQL for exploratory data analysis, modeling, and statistical analysis.

Preferred Qualifications:

1. Ability to analyze large data sets to identify behavior or system trends and synthesize them to influence product direction.
2. Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.
3. Experience leading key technical projects and substantially influencing the scope and output of others.
4. Track record of engaging senior leadership effectively to build understanding of and consensus for the viewpoints of the team.

• For New York, NY-based roles: The base salary range for this role is USD**$183,000 per year**
• USD**$203,000 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'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.