**About the Role** We seek an experienced Applied Scientist to join the eXperimentation, Personalization, and Optimization team (XPO). In this role, you'll work closely with various cross-functional teams (marketing managers, engineers, product managers, operations, data scientists, and analysts) to help optimize Uber’s marketing practices. The XPO team lives at the intersection of economics, statistics, and computer science. An ideal candidate has a demonstrable ability to successfully apply rigorous scientific methods (experimental design, media mix modeling, causal inference, or machine learning model development & deployment) to messy real-world problems. **What the Candidate Will Do** - Perform various analyses, hypothesis testing, and causal inference to statistically assess the relative impact and extract trends. - Build and deploy ML models to enhance understanding of user behavior and predict future performance of marketing campaigns. - Design experiments and interpret the results to draw detailed and measurable conclusions. - Present findings to senior management to inform business decisions - Collaborate with cross-functional teams across data science, product, engineering, operations, and marketing. **Basic Qualifications** - Ph.D., M.S. or Bachelors degree in Statistics, Economics, Mathematics, Machine Learning, Operations Research, or other quantitative fields - Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics - Experience with data analysis and visualization tools, such as Python, R, Tableau - Proficient at defining, utilizing, and communicating performance metrics - Proven track record of applying analytical/statistical methods to tackle real-world problems using big data - Experience with SQL on large multi-table data sets **Preferred Qualifications** - PhD degree in a quantitative field with 4+ years of working experience as an applied scientist - Previous experience in advertising tech (e.g., media-mix modeling, geo tests, attribution, targeting, 3rd party data integration, etc.) - Experience in experimentation design, Statistical modeling, Bayesian methods - Experience with Probabilistic programming (STAN, Pyro, etc.) - Comfort with ambiguity and the ability to work in a self-guided manner - Passion for Uber! For New York, NY-based roles: The base salary range for this role is USD$149,000 per year - USD$165,500 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$149,000 per year - USD$165,500 per year. For Seattle, WA-based roles: The base salary range for this role is USD$149,000 per year - USD$165,500 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](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](https://forms.gle/aDWTk9k6xtMU25Y5A). 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.