Senior Product Data Scientist Manager, Android

About the job

Android and Business Communication (ABC) is at the core of how people and businesses connect across the globe. Our mission is to build the world’s most helpful, expressive, and secure communication experiences. With communication apps such as Google Messages and Dialer, we ship products that make a meaningful difference in billions of lives worldwide.

We define standard-setting "toothbrush journeys"—from fundamental calling reliability to high-resolution media sharing and expressive reactions. Beyond peer-to-peer connection, we are pioneering the next generation of conversational commerce, enabling businesses to deliver app-like experiences directly within the messaging interface. Whether adapting mobile features for a multi-device world on Wear OS or driving engagement with features like call screens, we focus on innovation that connects everyone, regardless of their device.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Poland: zł620000 - zł640000 (PLN) + 25% bonus target + equity + benefits

US: $240000 - $334000 (USD) + 25% bonus target + equity + benefits

Learn more about [benefits at Google](https://www.google.com/about/careers/applications/benefits/).

Responsibilities

• Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Direct projects that combine analytical and organizational complexity towards clear, sound, and actionable decisions.
• Own projects end-to-end, covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presentation to stakeholders.
• Address ambiguous or new problems by using the capabilities of existing systems and collaborate to turn broad problems into work for the team.
• Oversee the integration of cross-functional and cross-organizational project/process timelines, drive improvements and recommendations, and define operational goals and objectives.
• Lead a team of data scientists, oversee technical accuracy across the organization, provide essential technical oversight for ranking, personalization, and classification strategies to scale the business globally.