Product Operations Manager

Product Operations Manager Department: Product Team: Product Operations Location: New York, United States Type: Full-Time **About the Role** Improve Uber’s product impact on a global scale. Work with cross-functional partners to surface needs, prioritize, test, launch, and iterate on Uber’s marketplace products. Develop and maintain Uber’s Global Intelligence related product suite to power Uber’s global delivery & mobility operations. **What the Candidate Will Do:** - Oversee Uber’s company wide relationships with external data providers and research agencies, including budgeting and procurement. - Guide team that translates externally collected data into regular reporting and ad hoc research projects for Uber’s executive & senior leadership teams (Sr Directors, Vice Presidents and Executives). - Spearhead cross-functional teams for any initiatives that focus on competitive strategy and benchmarking for Uber globally. - Leverage business metrics and competitive insights to optimize the end-to-end consumer experience and guide product improvements. - Develop and manage comprehensive rollout plans, ensuring execution across regions and alignment of functional stakeholders. - Drive semi-annual strategic planning, fostering a community of product leaders focused on scalable innovation and measurable outcomes. **Basic Qualifications:** - Bachelor's degree in Computer Science, Economics, Applied Mathematics, Engineering (Any), Data Science, Business Administration, or related field, and 5 years of progressive, post-baccalaureate experience in job offered or a product operations-related occupation. - Position requires: - **Analytics using** Gsheets, Excel, and Looker; - **Statistical analyses** including descriptive statistics, correlation, regression, confidence intervals, ability to build and understand econometric models in R, Python; - **Project management** related frameworks and software using Jira, Asana, and Microsoft Project; **Preferred Qualifications:** - **Analyzing user requirements**, procedures, and problems to automate or improve existing machine learning systems; - **D