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Manager II, Science - Ads Delivery & Optimization

Uber

Manager II, Science - Ads Delivery & Optimization

Uber

New York, NY

·

On-site

·

Full-time

·

4d ago

About the Role

The Uber Ads & Offers team builds consumer products that connect our eaters and riders to relevant businesses in engaging and delightful ways. We also build tools to help merchants, large and small, generate demand via Ads and Offers to grow their businesses.

Ads is one of the fastest growing lines of businesses at Uber. Every day thousands of advertisers use our Advertising platform to reach users on the Uber platform to help grow their businesses.

As a Science Manager for the Ads Delivery & Optimization team, you will play a pivotal role in shaping the future of Ads at Uber. Partnering closely with Engineering and Product leadership, you will drive the strategic vision and execution of Ads delivery-related product development (e.g. auction, pacing, bidding, ranking). You will lead a team of Scientists designing and implementing new algorithms to make our Ads system more efficient and performant. We are looking for experienced candidates, who have had experience building Ads systems to help accelerate our team and product growth.

  • What You'll Do

  • Lead a team of highly skilled scientists, providing mentorship, feedback, and career growth opportunities to foster technical excellence and impact.

  • Develop and execute robust experimental designs and insightful analyses to shape the product strategy, proactively identifying and mitigating potential challenges.

  • Develop and implement cutting-edge machine learning, statistical, and analytical solutions to enhance Ads relevance, ranking, bidding, pacing, and overall user experience.

  • Leverage data-driven insights and algorithmic expertise to guide the team's direction and balance short-term execution with long-term innovation.

  • Ensure robust data governance for event logging and metric generation, maintaining accuracy, consistency, and reliability.

  • Basic Qualifications

  • Ph.D., M.S. or Bachelors degree in Economics, Operations Research, Statistics, Mathematics, or other quantitative fields.

  • Minimum 7 years of industry experience as a Scientist or equivalent (5+ years if holding a Ph.D. degree).

  • Experience with exploratory data analysis, statistical analysis and testing, causal analysis and ML model development.

  • Minimum 1 year of experience in managing a team of Applied / Data Scientists with Strong people leadership skills including growing and mentoring your team members

  • Experience in Ad tech or marketplace industries.

  • Experience with tools like Python or R in a production environment

Preferred Qualifications:

  • 9+ years of industry experience as an (Applied / Data) Scientist or equivalent (7+ years if holding a Ph.D. degree).

  • 2+ years of experience in managing a team of Applied / Data Scientists with Strong people leadership skills including growing and mentoring your team members.

  • Bias to action and proven track record of getting things done.

  • Proficiency using Python, py Spark at scale with large data sets.

  • Experienced in partnering with cross-functional stakeholders to execute decisions.

  • Excellent communication and presentation skills.

  • Experience in algorithm development and prototyping.

  • Experience in building Ads Delivery systems (e.g. auction, pacing, bidding, ranking).

  • Experience with productionizing algorithms for real-time systems.

  • For New York, NY-based roles: The base salary range for this role is USD**$216,000 per year**

  • USD**$240,000 per year**.

  • For San Francisco, CA-based roles: The base salary range for this role is USD**$216,000 per year**

  • USD**$240,000 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

Junior/L3 · Driver

6,734 reports

$42,142

total / year

Base

$42,142

Stock

-

Bonus

-

$31,192

$56,937

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