Jobs

Senior Data Scientist, Product, Search


Job details
  • Google
  • London
  • 6 days ago

Minimum qualifications:

Please make sure you read the following details carefully before making any applications.

Master'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).3 years of experience managing analytical projects.Preferred qualifications:

7 years of experience with statistical data analysis, modeling, experimentation, and causal inference to solve product and business problems.5 years of experience in scripting, statistical analysis (e.g., R, Stata, SPSS, SAS), developing and managing metrics, and evaluating programs/products.3 years of experience working in a complex, matrixed organization.1 year of experience preparing and delivering technical presentations to executive leadership.Experience in identifying opportunities for product improvement and defining/measuring the success of those initiatives.Experience analyzing user behaviors in consumer apps, and linking those behaviors to successful business outcomes.About the job

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 will have an opportunity to make an impact on billions of people globally.

Responsibilities

Partner with Product, Engineering, and cross-functional teams to influence, prioritize, and support product strategy around the Android Google App's entry points, surfaces, and new product development.Apply technical expertise with observational data analysis, modeling, or causal inference to answer the most important product questions.Lead the design, analysis, and interpretation of product experiments or post-hoc causal inference analysis.Define and develop key metrics to measure users' journeys and experiences.Deliver effective presentations of data-driven insights and recommendations to multiple levels of stakeholders.

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