About the Role
We are looking for an Applied Scientist to join the paid marketing measurement team. In this role, you will work closely with multiple stakeholders, including the Marketing Channels team and the Adtech teams, to leverage experimentation, data and advanced analytics to drive business results. As a scientist in this position will help Uber invest and optimize its performance marketing envelope across digital parters all over the world for Uber's many businesses.
An ideal candidate would have a deep understanding of A|B and/or marketing experimentation with foundational knowledge of statistical modeling, and coding. Previous experience in advertising measurement or in a similar field is a plus.
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What You'll Do
- Plan, design, and implement incrementality experimentation across multiple ad platforms.
- Design custom experiments including synthetic control and causal inference to measure new and emerging marketing efforts.
- Leverage statistical modeling to interpret experiment and analytical ad data.
- Support any ad hoc analysis required to design a robust experiment.
- Collaborate with the Marketing Channels team to optimize and measure the effectiveness of new and existing campaigns.
- Present findings across marketing and the broader internal science community
- Collaborate with the Product and/or Engineering teams to ensure data is available and being interpreted consistent with theoretical expectation.
- Partner with internal customers, including Operations, Finance, Product, and the Channel team, to develop paid marketing strategies.
- Collaborate with other science teams in marketing and other organizations to improve Uber's measurement solutions.
Here is what the typical day would look like:
- 40% designing experiments, modeling, or measurement solutions
- 40% deep-dive analysis, results interpretation, and narrative crafting
- 20% stakeholder meetings
Basic Qualifications
- PhD, M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields
- Knowledge of underlying mathematical foundations of statistics, statistical modeling, and experimentation
- Experience with at least one experiment/quasi-experiment methodology: A/B Testing, incrementality experimentation, CLS, Synthetic Control, Market-Level testing, Causal inference, pre-post-analysis
- Proficiency in SQL
- Ability to use Python or R to work efficiently at scale with large data sets
Preferred Qualifications
- If PhD or M.S. in Statistics, Math, or Economics with a minimum of 1+ year of industry experience in a marketing science related role
- Drive to learn complex topics quickly.
- Strong communication skills including stakeholder management and storytelling
- Curious disposition, comfort with ambiguity and uncertainty in data.
- Previous experience in advertising tech and/or working with product and engineering teams to build scalable measurement solutions
For San Francisco, CA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year.
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 is proud to be an Equal Opportunity/Affirmative Action 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.