**About the Role** The Global Intelligence team works to understand the strategy and performance of Uber and other companies with similar products through a combination of external and internal data. Uber operates in a diverse array of markets and product categories filled with rapidly evolving competing options; assessing the success or failure of a product or strategy depends on understanding this context. Doing this, and doing it well, is an interesting and difficult problem. The team uses its expertise in data analysis, statistical modeling, economics, and business to build scalable data products. We are looking for experienced candidates with a passion for solving new and difficult problems with data. You will be able to use your strong quantitative and analytical skills to elevate competitive intelligence at Uber to strategic advantage and empower teams to make more informed business and strategy decisions. **What You Will Do** - Lead teams of scientists in competitive intelligence, while also contributing to projects. - Present findings to senior management to advise business decisions. - Provide rigorous technical mentorship to the team. - Collaborate with cross-functional teams across disciplines such as product, engineering, and operations to drive impact \-\-\-\- Basic Qualifications ---- - Ph.D., M.S., or Bachelors degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields. - Minimum 3 years of management or tech lead experience. - Basic understanding of experimental design (such as A/B experiments), statistical methods and modeling. - Ability to use Python to work efficiently at scale with large data sets. - Advanced SQL expertise. - Ability and experience in extracting insights from data, and summarizing learnings/takeaways - Strong communication skills across technical, non-technical, and executive audiences \-\-\-\- Preferred Qualifications ---- - Minimum 6 years of industry experience as an Applied or Data Scientist or equivalent. - Experience in competitive intelligence. - Advanced experience with experimental design and statistical methods for causal inference. - Willingness to get your hands dirty with messy data to find opportunities and uncover insights. - Ability to communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds. - To be highly detailed-oriented. - Excellent judgment, critical-thinking, and decision-making skills. For New York, NY-based roles: The base salary range for this role is USD$203,000 per year - USD$225,500 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$203,000 per year - USD$225,500 per year. For Seattle, WA-based roles: The base salary range for this role is USD$203,000 per year - USD$225,500 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.