Staff Data Scientist, Ads Insights and Measurement

Role Overview: At Google, data drives all decision-making processes. As a Quantitative Analyst, you will play a crucial role in shaping Google's business and technical strategies by processing, analyzing, and interpreting vast data sets. Your analytical skills and statistical methods will help identify opportunities for Google and its clients to operate more efficiently, ranging from improving advertising effectiveness to optimizing network infrastructure and studying user behavior. Your role goes beyond number crunching; you will collaborate with Engineers, Product Managers, Sales Associates, and Marketing teams to implement necessary adjustments based on your findings, ensuring both problem identification and solution implementation. Key Responsibilities: - Interact cross-functionally with various leaders and teams, collaborating with Engineers and Product Managers to identify design opportunities and evaluate enhancements for advertising measurement products. - Define questions related to advertising effectiveness, incrementality assessment, privacy impact, user behavior, brand building, bidding strategies, etc. Collaborate with teams to develop and implement quantitative methods to address these questions effectively. - Handle large, complex data sets, solving challenging and non-routine analysis problems by applying advanced analytical methods when necessary. Conduct various analyses, including data gathering, exploratory data analysis (EDA), model development, and delivering results to business partners and executives. - Prototype and build analysis pipelines iteratively to provide insights at scale. Develop a deep understanding of Google's data structures and metrics, advocating for necessary changes to support product development. Qualifications Required: - Master's degree in Statistics or Economics, a related field, or equivalent practical experience. - Minimum of 8 years of experience utilizing analytics to solve product or business problems, including coding skills in languages such as Python, R, SQL, statistical data analysis expertise, and experience with statistical software and database languages. - Experience in statistical data analysis techniques, including linear models, multivariate analysis, causal inference, or sampling methods. - Strong familiarity with statistical software like SQL, R, Python, MATLAB, and pandas, along with expertise in Statistical Analysis, Modeling, and Inference. (Note: Preferred qualifications and additional details about the company were not provided in the Job Description.),