Minimum qualifications: Bachelor's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience. 5 years of experience with statistical data analysis, data mining, and querying (e.g., SQL). 2 years of experience managing investigative projects. Preferred qualifications: Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field. 3 years of experience in scripting, statistical analysis (e.g., R, Stata, SPSS, SAS), developing and managing metrics, and evaluating programs/products. 1 year of experience working in a complex, matrixed organization. Experience working and communicating in areas with significant leadership and stakeholder scrutiny. Ability to articulate product questions, pulling data from large datasets (SQL, BigQuery or equivalent technologies), and using statistics to arrive at an answer. Ability to translate analysis results into business recommendations with excellent written and verbal communication, problem-solving and business judgment skills. 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. Our Data Science Team blends research and product expertise to address complex challenges. We leverage a mix of theoretical and practical knowledge in advanced statistical, machine learning techniques, predictive modeling, human eval, experimentation, forecasting, exploratory analysis, and more to drive data-informed innovation, unlock opportunities, and enhance user experiences within Chrome. We do not just analyze data—we pioneer the behavioral insights and experimentation frameworks required to build context-aware AI capabilities and agentic experiences. Our role is to help the browser anticipate user intent, streamline daily tasks, and seamlessly execute complex actions on the web. In this role, you will establish the critical guardrails, define the success metrics, and design the rigorous testing environments that validate our most ambitious product bets. You will partner directly with executive leaders to shape high-stakes strategies, moving past the theoretical to launch intelligent features that redefine the modern web experience. Chrome is dedicated to building a better, more open web. We’re focused on making a better browser (on both desktop and mobile) to help users take advantage of all the web has to offer in a safe and secure way.Chrome is available across all major platforms — iOS, Android, Windows, Mac, Linux and Chrome OS. We also built Chrome as an open source project so the entire web ecosystem could benefit from the latest innovations in speed, simplicity and security.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. Germany: €100000 - €103000 (EUR) + 15% bonus target + equity + benefits Learn more about benefits at Google.* Leverage advanced statistical methods on massive, complex datasets to extract insights from billions of events and thousands of features across organizational sources. Analyze intricate AI product and platform usage patterns, translating data-driven insights into actionable product strategy and engineering decisions. Works cross-functionally with Research, Engineering, and Product teams (e.g., Google DeepMind, Search, Shopping) to translate ambiguous data challenges into strategic business opportunities. Make clear, concise product and engineering recommendations to drive major impact. Interest and aptitude in data, metrics, analysis and trends and applied knowledge of measurement, statistics and program evaluation.