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Sr Data Scientist

Uber

Sr Data Scientist

Uber

Sunnyvale, CA

·

On-site

·

Full-time

·

4d ago

About the Role

As a Senior Data Scientist on the Merchant Optimization team, you will play a pivotal role in identifying the optimal merchant selection for consumers and innovating on pricing models that enable merchants to effectively participate in the marketplace. Your work will directly shape Uber's strategy by maximizing merchant ROI while driving growth and profitability across the Delivery business.

You will leverage advanced experimentation, machine learning, and a deep understanding of marketplace dynamics to develop data-driven solutions that influence product direction and improve marketplace efficiency.

The ideal candidate has strong technical expertise, a track record of driving impact through sophisticated analytical methods, and the ability to partner closely with product, engineering, and operations teams to bring scalable solutions to life.

---- What You Will Do ----

  1. Lead and mentor a team of data scientists and applied scientists, fostering a culture of innovation and impact.
  2. Design and execute rigorous A/B experiments to optimize pricing, incentives, and other marketplace levers.
  3. Collaborate cross-functionally with engineering, product, and operations teams to drive strategic decision-making.
  4. Generate actionable insights from large-scale data sets to inform both short-term execution and long-term product direction.
  5. Define and measure key success metrics, ensuring alignment with business goals.
  6. Advocate for best practices in data science, model monitoring, and causal inference within the organization.
  7. Propose and guide framework of data analysis and experiments to drive business insight and facilitate decisions.
  8. Collaborate closely with Engineering and Product teams to productionize models, enhance data observability and metrics with dashboards, and conduct experiments and in-depth analysis.
  9. Communicate with leadership and cross-functional teams, including presentation of the Science team's work on models, solutions, and data analytics findings.

---- Basic Qualifications ----

  1. Ph.D/M.S degree in Statistics, Economics, Mathematics, Operations Research, or other quantitative fields.
  2. Minimum 5 years of industry experience as a Scientist or equivalent (3+ years if holding a Ph.D. degree).
  3. Experience with exploratory data analysis, statistical analysis and testing, causal analysis and ML model development.
  4. Experience with tools like SQL or R in a production environment.
  5. Bias to action and proven track record of getting things done.
  6. Proficiency using Python, py Spark at scale with large data sets.
  7. Experienced in partnering with cross-functional stakeholders to execute decisions.
  8. Experience in tech or marketplace industries.
  9. Exceptional problem-solving skills and the ability to translate complex data into clear, actionable insights.
  10. Proven ability to lead and develop high-performing teams.
  11. Excellent communication skills, with the ability to influence technical and non-technical stakeholders.

---- Preferred Qualifications ----

  1. Experience in a marketplace, ride-sharing, or delivery platform.
  2. Knowledge of reinforcement learning, optimization algorithms, or econometrics.
  3. Prior experience working with large-scale distributed systems and real-time data processing.
  • For San Francisco, CA-based roles: The base salary range for this role is USD**$190,000 per year**

  • USD**$211,000 per year**.

  • For Sunnyvale, CA-based roles: The base salary range for this role is USD**$190,000 per year**

  • USD**$211,000 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. 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.

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.

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About Uber

Uber

Uber develops, markets, and operates a ride-sharing mobile application that allows consumers to submit a trip request.

10,001+

Employees

San Francisco

Headquarters

$120B

Valuation

Reviews

3.1

10 reviews

Work Life Balance

4.2

Compensation

2.3

Culture

3.5

Career

2.0

Management

2.5

45%

Recommend to a Friend

Pros

Flexible hours and schedule

Meeting different people and cultures

Make your own hours

Cons

Inconsistent and low pay

Safety concerns with passengers

Traffic and difficult drivers

Salary Ranges

23,534 data points

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Data Scientist L3

0 reports

$145,456

total / year

Base

-

Stock

-

Bonus

-

$123,638

$167,274

Interview Experience

5 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Offer Rate

40%

Experience

Positive 80%

Neutral 20%

Negative 0%

Interview Process

1

Application Review

2

Online Assessment

3

Recruiter Screen

4

Technical Phone Screen

5

Case Study/Analytics Test

6

Final Loop/Panel Interview

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Case Study

Technical Knowledge