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2026 PhD Scientist Intern (Competitive Intelligence)

Uber

2026 PhD Scientist Intern (Competitive Intelligence)

Uber

San Francisco, CA; Sunnyvale, CA

·

On-site

·

Internship

·

4d ago

We're looking for PhD candidates to work with the Competitive Intelligence Team as a Scientist intern during summer 2026 (12 weeks). As an intern, you will be embedded in a product team working on solving real-world Uber problems under the supervision of an analyst on that team, and will have the opportunity to partner closely with Scientists, Software Engineers, Product Managers, and other cross-functional partners.

About the Role:

The Competitive Intelligence team works to understand the strategy and performance of Uber and other companies with similar products through a combination of external and internal data. Uber operates in a diverse array of markets and product categories filled with rapidly evolving competing options; assessing the success or failure of a product or strategy depends on understanding this context. Doing this, and doing it well, is an interesting and challenging problem. The team uses its data analysis, statistical modeling, economics, and business expertise to build scalable data products and ship actionable insights.

We are looking for candidates passionate about solving new and difficult problems with data. You will build out and own competitive metrics/models, provide key insights, conduct deep dive analysis to understand new opportunities and empower teams to make more informed business and strategy decisions with competitive intelligence.

  • What You'll Do

  • Work with a mentor closely to define a business problem, scope a project, develop, and prototype the solution using data-driven approaches

  • Work with engineers and product managers to turn prototypes into scalable solutions

  • Present findings to leaders to inform decisions

  • Establish standard methodologies for science such as modeling, coding, analytics, optimization, and experimentation

  • Basic Qualifications

  • Pursuing a Ph.D. majoring in Statistics, Machine Learning, Economics, or other related quantitative fields

  • Candidates should have at least one semester/quarter left of their education after finishing the internship

  • Strong problem-solving and analytical abilities

Preferred Qualifications:

  • Coding proficiency in areas such as R, Spark, SQL, Python
  • Background in data visualization via open-source libraries/packages or third-party tools (i.e. Tableau, Mixpanel, Looker, or similar)
  • Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, stochastic processes, economics, and analytics
  • Experience in the following areas: Exploratory Data Analysis, Statistical Analysis, ML Model Development, Competitive Intelligence, Causal Inference, Operations Management, Transportation
  • 0-2 years of prior work experience in an analytical setting
  • Organized, detail-oriented and able to work independently on multiple projects at once
  • Ability to communicate effectively with both technical and business partners
  • Open to feedback, excellent at implementing newly learned ideas and concepts
  • Research mentality with a bias towards action to structure a project from idea to prototype to implementation
  • Independence, self-starter mindset, excellent communication, and outstanding follow-through - you energetically tackle your work and love the responsibility of being individually empowered

For San Francisco, CA-based roles: The base hourly rate amount for this role is USD**$67.00** per hour.

For Seattle, WA-based roles: The base hourly rate amount for this role is USD**$67.00** per hour.

For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD**$67.00** per hour.

For all US locations, you will also be eligible for various 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