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Senior Staff Engineer - Marketplace Competitive Intelligence

Uber

Senior Staff Engineer - Marketplace Competitive Intelligence

Uber

San Francisco, CA; Seattle, WA

·

On-site

·

Full-time

·

1mo ago

Compensation

$267,000 - $297,000

Benefits & Perks

Flexible work arrangements

Team events and activities

Professional development budget

Generous paid time off and holidays

Comprehensive health, dental, and vision insurance

Flexible Hours

Learning

Healthcare

Required Skills

Python

JavaScript

TypeScript

About Us

Uber is changing how people think about transportation, part of the logistical fabric of 600+ cities - giving people what they want when they want it.

Size: 10000+ employees
Industry: Technology

View Company Profile

About the Role

Uber is looking for a Senior Staff Engineer to lead the technical vision and execution for our Competitive Intelligence domain. A mission-critical space at the intersection of core business strategy and market-level decision systems such as pricing, incentives, and marketplace configuration. This role spans both offensive and defensive workstreams, requiring a systems thinker who can operate across high-stakes ambiguity and deep technical complexity.

On the offensive side, you'll help us derive meaningful, actionable insight from incomplete, noisy, and often unreliable data sources to better understand market dynamics, competitor behavior, and pricing strategy. The systems you build must extract signal from chaos, integrating low-trust external data into internal pricing and incentive systems, and shaping coherent narratives that guide Uber's most strategic decisions.

On the defensive front, you'll oversee the architecture and technical leadership needed to prevent scraping and data abuse, protecting the integrity of our platform and preserving the value of Uber's proprietary data. This includes work in adversarial machine learning, bot detection, and the design of resilient, real-time defenses at scale.

This role offers a rare opportunity to define the direction of critical, high-impact systems that shape Uber's competitive edge, while mentoring engineers and partnering closely with senior leadership across product, engineering, data science, and security.

What You Will Do:

  • Lead the design and development of systems that extract strategic insights from unreliable and fragmented market data
  • Architect and guide the implementation of real-time defenses against scraping and data abuse, working on adversarial machine learning and bot detection solutions to protect Uber's data and platform integrity at scale.
  • Drive critical cross-functional initiatives by partnering with data science, security, product, and engineering teams to align technical solutions with business priorities and long-term strategy.
  • Mentor senior engineers across multiple teams, providing technical direction, setting engineering standards, and fostering a culture of high-quality system design, experimentation, and resilience.

Basic Qualifications:

  • Master's Degree or equivalent in Computer Science, Engineering, Mathematics or related field with 7+yrs of software development experience.
  • Proficiency in one of the programming languages (e.g. C, C++, Java, Python, or Go)
  • Experience driving large-scale system modernization, performance optimizations, and deployment safety improvements.
  • Ability to lead large technical initiatives and drive cross-team collaboration across platform, security, and infrastructure teams.

Preferred Qualifications:

  • Cybersecurity Knowledge: Understanding of web scraping techniques and countermeasures.
  • Awareness of network security, HTTP protocols, and API security.
  • Experience in modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
  • Proficiency in unsupervised learning techniques, such as clustering, anomaly detection, and neural networks.
  • Familiarity with supervised learning, as it often complements unsupervised methods.
  • Understanding of feature engineering and dimensionality reduction.
  • Familiarity with machine Learning software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
  • Causal ML and Reinforcement Learning
  • Ethical Considerations and Compliance: awareness of ethical issues and regulatory compliance related to data privacy and machine learning.

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  • For San Francisco, CA-based roles: The base salary range for this role is USD**$267,000 per year**

  • USD**$297,000 per year**.

  • For Seattle, WA-based roles: The base salary range for this role is USD**$267,000 per year**

  • USD**$297,000 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.

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.

Client-provided location(s): Seattle, WA, San Francisco, CA

Job ID: Uber-144297

Employment Type: FULL_TIME

Posted: 2026-01-31T19:57:26
Apply on company site

Perks and Benefits

Health and Wellness

  • Health Insurance
  • Health Reimbursement Account
  • Dental Insurance
  • Vision Insurance
  • Life Insurance
  • FSA With Employer Contribution
  • Fitness Subsidies
  • On-Site Gym
  • Mental Health Benefits

Parental Benefits

Fertility Benefits:

Work Flexibility

  • Flexible Work Hours
  • Remote Work Opportunities
  • Hybrid Work Opportunities

Office Life and Perks

  • Casual Dress
  • Pet-friendly Office
  • Snacks
  • Some Meals Provided
  • On-Site Cafeteria

Vacation and Time Off

  • Paid Vacation
  • Unlimited Paid Time Off
  • Paid Holidays
  • Personal/Sick Days
  • Sabbatical
  • Volunteer Time Off

Financial and Retirement

  • 401(K)
  • Company Equity
  • Performance Bonus

Professional Development

  • Work Visa Sponsorship
  • Associate or Rotational Training Program
  • Promote From Within
  • Mentor Program
  • Access to Online Courses

Diversity and Inclusion

  • Employee Resource Groups (ERG)
  • Diversity, Equity, and Inclusion Program

Apply on company site

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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

Mid/L4

Mid/L4 · Data Analyst

3 reports

$209,300

total / year

Base

$161,000

Stock

-

Bonus

-

$203,580

$209,300

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