Senior Data Scientist, Research, Google Search, Real World Journeys

The Real World Journeys (RWJ) team’s mission is to inspire action by connecting people with experiences that make life better. We are currently shaping the evolution of Google Search leveraging AI for initiatives like AI Mode and AI Overviews to ensure it remains the world's leading source of information. We empower users to accomplish their goals by acquiring and generating valuable content and forging strong partnerships that benefit both users and partners. In this role, you will work cross-functionally with Engineering, Product, and UX leads to uncover new product avenues and shape strategic direction. Your work will be essential to determining the future of Google Search, utilizing emerging technologies to drive product innovation. You will apply advanced modeling techniques—including LLMs, causal inference, Machine Learning (ML)—to solve complex business problems and design robust, data-driven user research. Additionally, you will lead a series of initiatives to identify growth areas and challenges within our flagship verticals, harnessing AI to maximize Search capabilities In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google .

Frame and solve ambiguous business problems and communicate the results to a non-technical audience. Interact cross-functionally, be a thought partner and influence a wide range of cross-functional teams. Communicate clearly and persuasively to influence leadership. Effectively apply machine learning, statistical analysis, and causal inference to address business challenges. Perform in-depth data exploration from complex data to uncover insights and drive strategy.

Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree. Preferred qualifications: 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.