{"id":2437489,"url":"https://alion.io/job/uber-program-manager-ii-tech-2","title":"Program Manager II, Tech","company":{"id":230,"name":"Uber","domain":"uber.com","url":"https://alion.io/company/uber","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":93,"open_postings":127,"ghost_share":0,"stale_share":0.441,"repost_share":0.039,"time_to_fill_p50_days":7,"computed_at":"2026-10-13T05:45:00Z"}},"role":"Management","role_family":"Management","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16500,"max_usd":36000,"period":"year","method":"role_seniority_country_cell","sample_n":9},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Recommender Systems","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-13T09:22:43Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-13T19:10:57Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the Role\nThe GSS Data Analytics team serves as Uber's analytics and AI solutions partner, helping Product,\nOperations, Engineering, and Data Science teams solve complex business challenges through\nscalable analytics, automation, and AI-powered solutions.\nAs a Program Manager II, you will lead high-impact initiatives from problem definition through\nexecution, driving cross-functional alignment while delivering solutions that improve operational\nefficiency, decision-making, and business outcomes across Uber's global lines of business.\nThis role sits at the intersection of program management, advanced analytics, automation, and\nemerging AI technologies. You will partner with stakeholders across the company to identify\nopportunities, define success metrics, and build scalable solutions that unlock measurable business\nimpact.\n----- What You Will Do ----\nLead end-to-end analytics, automation, and AI initiatives by partnering with Product,\nOperations, Engineering, and Data Science teams to define business problems,\nestablish success metrics, and drive execution from ideation through implementation.\nUtilize advanced analytical and visualization techniques to develop scalable\nend-to-end solutions, uncover actionable insights from large and complex datasets,\nand influence product, operational, and strategic decisions across Uber.\nTranslate complex analytical findings and technical solutions into clear, concise, and\ncompelling recommendations for both technical and non-technical stakeholders,\nenabling data-driven decision making at all levels of the organization.\nDrive multiple concurrent analytics, data engineering, and AI projects while navigating\nambiguity, prioritizing effectively, and maintaining a high bar for quality, accuracy, and\noperational excellence.\nDesign KPI frameworks, measurement strategies, and performance tracking systems\nthat help teams monitor business health, evaluate initiatives, and identify opportunities\nfor growth and efficiency improvements.\nIdentify opportunities to leverage Machine Learning and Generative AI technologies,\ndefine solution strategies, translate business requirements into technical\nspecifications, and partner with technical teams to deliver impactful AI-powered\nsolutions.\nBuild intelligent data products and automation solutions, including conversational\nassistants, recommendation systems, self-service tools, and workflow automations by\nleveraging Python, LLM APIs, and modern AI technologies.\nLead vendor data analysts and project contributors, establish best practices and\ndocumentation standards, and continuously improve the scalability, efficiency, and\nquality of DAS team deliverables.\nCut through noise in large datasets to identify the core business questions,\ndemonstrate strong attention to detail, and maintain a hands-on, scrappy approach to\nsolving problems and unblocking teams when needed.\n---- What You Will Need ----\n6+ years of experience in Program Management, Analytics, Business Intelligence, Data\nScience, Data Engineering, or related quantitative fields.\nAdvanced SQL and Python proficiency with experience developing analytical,\nautomation, or AI-driven solutions using large-scale datasets.\nExperience leading cross-functional programs and partnering with Product,\nOperations, Engineering, and Data Science stakeholders to deliver business impact.\nStrong analytical and problem-solving skills, with the ability to translate complex\nbusiness challenges into scalable data, automation, or AI solutions.\nExperience communicating insights and recommendations to both technical and\nnon-technical audiences and influencing decisions through data-driven storytelling.\n---- Preferred Qualifications ----\nExperience applying Machine Learning, Generative AI, or advanced analytics\ntechniques to solve business problems and drive measurable outcomes.\nHands-on experience integrating Large Language Models (LLMs) and AI services\nthrough APIs to build intelligent applications, copilots, chatbots, or workflow\nautomation solutions.\nExperience building or leading the development of AI-powered products such as\nrecommendation systems, forecasting solutions, decision-support systems, or\nself-service analytics platforms.\nStrong understanding of ML development lifecycles, experimentation frameworks,\nmodel evaluation methodologies, and deployment considerations.\nExperience managing large-scale initiatives in fast-paced, ambiguous environments\nand driving alignment across multiple teams and organizations.\nBachelor's or Master's degree in Statistics, Computer Science, Engineering,\nEconomics, 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