Data Science Manager, Product, Cloud

About the job

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.

The mission of Cloud Supply Chain Data (CSCD) Data Science and Product team is to build productivity and data products, develop AI/ML/statistical models and provide prescriptive insights to help CSCD define and achieve business goals. We help make Google Cloud supply chain and Data Centers by enabling data-informed decision making and product innovation.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities

• Manage Bengaluru Center of Excellence for Cloud Supply Chain and Operations, Data Science and Product team.
• Lead a portfolio of programs in developing ML/Statistical models, conducting diagnostic analytics research, crafting prescriptive insights.
• Guide problem framing, metrics development, data extraction and manipulation, visualization, and story telling for the team.
• Provide thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).
• Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and define operational goals and objectives.