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JobsUber

Staff Scientist - Ads & Offers

Uber

Staff Scientist - Ads & Offers

Uber

New York, NY; San Francisco, CA; Seattle, WA; Toronto, Canada

·

On-site

·

Full-time

·

1mo ago

Compensation

$197,000 - $197,000

Benefits & Perks

Team events and activities

Generous paid time off and holidays

Professional development budget

Parental leave

Comprehensive health, dental, and vision insurance

Learning

Parental Leave

Healthcare

Required Skills

PostgreSQL

TypeScript

Node.js

About the Role

Every day thousands of merchants use our Advertising and Offers platform to reach users on Uber to grow their businesses. The Science team on Ads & Offers designs and builds the core algorithmic components of this system.
As a Staff Scientist on the team, you will work on understanding how various parts of the system (e.g. auction, pacing, bidding, ranking) are performing. You will lead the design and implementation of new algorithms to make our Ads system more efficient and performant. You will also work on the interaction of ads with the different marketing levers available to merchants, like offers.
We are looking for experienced candidates, who have had experience building Ads systems to help accelerate our growth. The ideal candidate should possess a strong passion for understanding complex systems, have the curiosity to understand why systems behave in certain ways, have the drive to research / propose new system designs and is a pragmatist.

What You'll Do

  • Build statistical, optimization, and machine learning models for a range of applications in the Ads & Offer space (e.g. auction, bidding, pacing, ranking).
  • Design and execute product experiments and interpret the results to draw detailed and actionable conclusions.
  • Use data to understand product performance and to identify improvement opportunities.
  • Present findings to senior management to inform business decisions.
  • Collaborate with cross-functional teams across disciplines such as product, engineering, and marketing to drive system development end-to-end from ideation to productionization.

Basic Qualifications

  • Ph.D., or M.S. in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields.
  • Minimum 4 years of industry experience as an Applied or Data Scientist or equivalent.
  • Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics.
  • Experience in experimental design and analysis.
  • Experience with exploratory data analysis, statistical analysis and testing, and model development.
  • Ability to use Python or R to work efficiently at scale with large data sets.

Preferred Qualifications

  • 6+ years of industry experience.
  • Proficiency in SQL.
  • Experience in algorithm development and prototyping.
  • Experience in building Ads Delivery systems.
  • Experience with productionizing algorithms for real-time systems.
  • Excellent communication and presentation skills.

For Canada-based roles: Uber may use artificial intelligence (AI) tools to support parts of our recruiting process; however, Uber employees make the ultimate selection and hiring decisions. This advertisement relates to a current, existing vacancy.

  • For Canada-based roles: The base salary range for this role is CAD**$197,000 per year**
  • CAD**$219,000 per year**.
  • 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 Seattle, WA-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. 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.

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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