Program Manager II, Tech

About the Role

• The GSS Data Analytics team serves as Uber's analytics and AI solutions partner, helping Product,
• Operations, Engineering, and Data Science teams solve complex business challenges through
• scalable analytics, automation, and AI-powered solutions.
• As a Program Manager II, you will lead high-impact initiatives from problem definition through
• execution, driving cross-functional alignment while delivering solutions that improve operational
• efficiency, decision-making, and business outcomes across Uber's global lines of business.
• This role sits at the intersection of program management, advanced analytics, automation, and
• emerging AI technologies. You will partner with stakeholders across the company to identify
• opportunities, define success metrics, and build scalable solutions that unlock measurable business
• impact.

----- What You Will Do ----

• Lead end-to-end analytics, automation, and AI initiatives by partnering with Product,

Operations, Engineering, and Data Science teams to define business problems,

establish success metrics, and drive execution from ideation through implementation.

• Utilize advanced analytical and visualization techniques to develop scalable

end-to-end solutions, uncover actionable insights from large and complex datasets,

and influence product, operational, and strategic decisions across Uber.

• Translate complex analytical findings and technical solutions into clear, concise, and

compelling recommendations for both technical and non-technical stakeholders,

enabling data-driven decision making at all levels of the organization.

• Drive multiple concurrent analytics, data engineering, and AI projects while navigating

ambiguity, prioritizing effectively, and maintaining a high bar for quality, accuracy, and

operational excellence.

• Design KPI frameworks, measurement strategies, and performance tracking systems

• that help teams monitor business health, evaluate initiatives, and identify opportunities
• for growth and efficiency improvements.
• Identify opportunities to leverage Machine Learning and Generative AI technologies,
• define solution strategies, translate business requirements into technical
• specifications, and partner with technical teams to deliver impactful AI-powered
• solutions.

• Build intelligent data products and automation solutions, including conversational

assistants, recommendation systems, self-service tools, and workflow automations by

leveraging Python, LLM APIs, and modern AI technologies.

• Lead vendor data analysts and project contributors, establish best practices and

documentation standards, and continuously improve the scalability, efficiency, and

quality of DAS team deliverables.

• Cut through noise in large datasets to identify the core business questions,

demonstrate strong attention to detail, and maintain a hands-on, scrappy approach to

solving problems and unblocking teams when needed.

---- What You Will Need ----

• 6+ years of experience in Program Management, Analytics, Business Intelligence, Data

Science, Data Engineering, or related quantitative fields.

• Advanced SQL and Python proficiency with experience developing analytical,

automation, or AI-driven solutions using large-scale datasets.

• Experience leading cross-functional programs and partnering with Product,

Operations, Engineering, and Data Science stakeholders to deliver business impact.

• Strong analytical and problem-solving skills, with the ability to translate complex

business challenges into scalable data, automation, or AI solutions.

• Experience communicating insights and recommendations to both technical and

non-technical audiences and influencing decisions through data-driven storytelling.

---- Preferred Qualifications ----

• Experience applying Machine Learning, Generative AI, or advanced analytics

techniques to solve business problems and drive measurable outcomes.

• Hands-on experience integrating Large Language Models (LLMs) and AI services

through APIs to build intelligent applications, copilots, chatbots, or workflow

automation solutions.

• Experience building or leading the development of AI-powered products such as

recommendation systems, forecasting solutions, decision-support systems, or

self-service analytics platforms.

• Strong understanding of ML development lifecycles, experimentation frameworks,

model evaluation methodologies, and deployment considerations.

• Experience managing large-scale initiatives in fast-paced, ambiguous environments

and driving alignment across multiple teams and organizations.

• Bachelor's or Master's degree in Statistics, Computer Science, Engineering,

Economics, Mathematics, or a related quantitative discipline.