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About The RoleThe Rider Core Experience & Personalization team's goal is to help Uber become the "operating system" for everyday life. This means building personalized experiences and helping our customers to discover new services that they would like.The Applied Science team leverages a mix of machine learning algorithms, statistical methods and experimentations. We optimize both the content and user experience on the highest impact surfaces in the mobile app - including the home feed, product selector and on-trip surfaces - to achieve better outcomes for both Uber's marketplaces and its customers.What You'll Do

• Develop and evaluate large-scale machine learning models and recommender systems in production to personalize the rider experience
• Propose, design, and analyze large scale online experiments
• Define and implement metrics to measure product performance
• Explore rich mobile, transactional, and geo-temporal data sets to uncover opportunities
• Present findings to business and executive audiences
• Collaborate with engineers and product managers to implement ideas and plan future roadmaps

Basic Qualifications

• Ph.D., MS or Bachelors degree in Statistics, Economics, Operations Research, Computer Science, Engineering, or other quantitative field. (If an M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years of industry experience as an Applied Scientist or equivalent)
• Knowledge of underlying mathematical foundations of machine learning, statistics, optimization, economics, and analytics
• Knowledge of experimental design and analysis
• Experience with exploratory data analysis, statistical analysis and testing, and model development
• Ability to use a language like Python or R to work efficiently at scale with large data sets
• Proficiency in technologies like SQL, Spark, and Hadoop

Preferred Qualifications

• Experience developing and evaluating large-scale machine learning models in production
• Knowledge in modern machine learning techniques applicable to personalization, ranking and recommender systems
• Advanced understanding of statistics, causal inference, and machine learning
• 5+ years of industry experience as an Applied Scientist or equivalent.
• Experience designing and analyzing large scale online experiments
• Experience working with large scale data sets using technologies like Hive, Presto, and Spark

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.For San Francisco, CA-based roles: The base salary range for this role is $174,000 per year - $193,500 per year.For Seattle, WA-based roles: The base salary range for this role is $174,000 per year - $193,500 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.