Tech Stack
Job Description, Responsibilities & Requirements
About the Position
We're seeking a Data Scientist Manager to lead a team dedicated to protecting Android users from threats in the era of AI. As a Data Scientist Manager, Research on the Android Ecosystem Trust team, you will drive technical strategy and foster innovation by identifying the most impactful data science problems worth answering, ensuring that research efforts are strategically aligned with defeating adversaries.
Responsibilities
- Define relevant Data Science questions about defeating adversaries. Lead the team to develop and implement quantitative methods (e.g., data analysis, experimentation, statistics, and machine learning modeling) to answer those questions and shape new data-driven products and solutions.
- Collaborate cross-functionally with leaders, engineers, and product managers to identify design opportunities and assess improvements for Android Ecosystem Trust systems and products.
- Make business recommendations through data, with effective presentations of findings to multiple levels of stakeholders to drive business decisions and stakeholder thinking.
- Act as a thought partner to organizational leadership. Help leaders crystallize analysis insights and research findings into strategic decisions and communicate them to high-level audiences.
- Help the team realize their potential by setting clear expectations, openly evaluating performance, upholding accountability, and providing opportunities to stretch their skills.
Requirements
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, including coding (e.g., Python, R, SQL), querying databases, and statistical analysis, or 6 years of work experience with a PhD.
- 3 years of experience as a people manager within a technical leadership role.
- PhD in Statistics, Mathematics, Data Science, Economics, or a related quantitative field.
- Experience across a wide range of data science problems, including metrics design, experimentation, statistical or machine learning modeling, and non-routine data analysis.
- Experience articulating and translating business questions and using statistical techniques to arrive at answers using available data.
- Ability to provide detailed technical guidance to a team, enabling them to execute.
- Ability to select optimal statistical tools for data science problems.
- Commitment to continuous learning, respect for science, tolerance for ambiguity, and a deep interest in the practical application of science to business.
We Offer
- Opportunity to work in a cutting-edge field at the intersection of data science and cybersecurity.
- Collaborative and innovative work environment.
- Professional growth and development opportunities.
About the Company
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.