Program Manager, Machine Learning Data Operations

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Minimum qualifications:

• Bachelor's degree in Computer Science or equivalent practical experience.
• 5 years of experience in program or project management.
• Experience working with data analytics tools and reporting platforms.

Preferred qualifications:

• 3 years of industry experience in managing large-scale and dynamic programs, involving vendor managed resources.
• Experience in managing complex, global and cross-functional projects with excellent project management skills.
• Ability to operate with high-energy and flexibility in a fast-paced, constantly evolving team environment, navigate through ambiguity, and work separately.

About the job

A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

Our goal is to build a Google that looks like the world around us - and we want Googlers to stay and grow when they join us. As part of our efforts to build a Google for everyone, we build diversity, equity, and inclusion into our work and we aim to cultivate a sense of belonging throughout the company.

Responsibilities

• Understand various Google products, tools and processes, and leverage them to push machine learning based automation and increase operational efficiencies.
• Deliver critical pieces of analysis and use these to drive new insights and uncover improvement opportunities, identify and implement large-scale measurable and scalable solutions for machine learning projects.
• Contribute to global company-wide planning processes that include budgeting, project prioritization, headcount planning, forecast management, and variance analysis.
• Support teams in fast-paced environments to drive large-scale program delivery from concept to completion, leading through multiple evolution along the way. Prioritize, adapt to change, and provide flexible thought partnership in a rapidly evolving landscape.
• Understand, develop, and collaborate with engineering and cross-product groups to find solutions to optimize and scale human computation micro-tasks on machine learning and imagery curation/moderation pipelines.