Data Science Researcher

At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution. Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day. Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products. Responsibilities Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions, provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. Use custom data infrastructure or existing data models, design and evaluate models to mathematically express and solve defined problems with limited precedent. Gather information, business goals, priorities, and organizational context, as well as the existing and upcoming data infrastructure. Own the process of gathering, extracting, and compiling data across sources through relevant tools (e.g., SQL, R, Python), format, re-structure, or validate data to ensure quality, and review the dataset to ensure it's ready for analysis.