Program Manager II, Tech - Data Labeling

About the Role

The candidate will be leading Uber's Data Labeling Program at GSS, which includes working with teams within Uber for their data annotation needs to power AI/ML products.

As Program Manager in the GSS ML Ops team, the candidate will play a crucial role in driving the successful execution of complex projects and programs from inception to delivery. Responsibilities encompass a wide range of activities, both strategic and operational, and require a blend of technical knowledge, leadership skills, and business understanding. The candidate is expected to lead complex, cross-functional tech programs with strong stakeholder partnerships and drive operations for successful delivery within budget and timelines.

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

1. Program Leadership: Define program scope, OKRs, and KPIs. Ensure alignment with stakeholder objectives and product goals
2. Cross-functional Collaboration: Lead and coordinate cross-functional teams across ops, engineering, and product for data annotation needs within Uber.
3. Execution and Delivery: Independently manage a team of data annotators to drive quality and efficiency. Deliver qualitative and quantitative insights to enhance model development, identify failure points of the model, and improve end-user experience.
4. Financial: Own program budget for data annotation. Drive efficiency by running experiments to transition to low-cost operating models while maintaining a high standard of quality.
5. Risk Management: Identify and mitigate program risks and issues, ensuring timely escalation and resolution.
6. Continuous Improvement: Analyze program performance and implement optimizations to improve efficiency and outcomes.
7. Communication: Provide regular program updates to stakeholders, including executive leadership. Conduct weekly, monthly, and quarterly business reviews.

1. Minimum 5 years of experience in program management or product management
2. Experience in solving problems, both structured and ambiguous, at scale, with strong attention to detail in fast-changing business environments
3. Excellent written and verbal communication skills. Ability to influence and motivate people (both technical and non-technical audiences) across a broad variety of job functions through relationships
4. Strong analytical and quantitative skills with the ability to use data and metrics to back up assumptions, recommendations, and drive customer and product-focused decisions
5. Self-motivated and curious, with a strong affinity for strategic problem solving, operations management, and driving action

1. Understanding of the AI landscape and how high-quality data and continuous evaluation of models help improve performance
2. Experience working with engineering, science, and product teams
3. Willing to explore and learn new technologies, hybrid processes