Data Scientist, Research, Ads Insight

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience.
  
• 2 years of experience with statistical data analysis, data mining, and querying (e.g., Python, R, SQL).
  

Preferred qualifications:

• PhD degree.
  
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  
• Experience with causal inference methods (e.g., split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators).
  
• Experience articulating and translating business questions and using techniques to arrive at an answer using available data.
  

About the job

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.

Responsibilities

• Help suggest, support and shape new data-driven and privacy preserving advertising and marketing products in collaboration with engineering, product and customer-facing teams.
• Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced investigative methods as needed. Conduct analyses that include data gathering and requirements specification, Exploratory Data Analysis (EDA), model development, and delivery of results to business partners and executives.
• Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development.
• Interact cross-functionally, make business recommendations (e.g., cost-benefit analysis, experimental design, use of privacy preserving methods such as differential privacy), with effective presentations of findings at multiple levels of stakeholders to drive business decisions and stakeholder thinking.