Data Scientist, Product, Customer Engagement
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Minimum qualifications:
- 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).
- 5 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- Experience in developing and managing metrics or evaluating programs/products.
Preferred qualifications:
- 5 years of experience in scripting or statistical analysis (e.g., R, Stata, SPSS, SAS) in a matrixed organization.
- 3 years of experience preparing and delivering technical presentations to executive leadership.
- Experience working with Engineers, Product Managers, and UX especially around providing product-centric insights.
- Track record of solving unstructured business problems with data science, translating results into impactful business recommendations, and measuring the success of those initiatives.
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.
Through your professional expertise and judgment, you work on multiple projects concurrently, developing analyses, models and methods to support and verify the impact of your recommendations. You share your expertise by consulting on projects, serving on committees and mentoring team members.
Responsibilities
- Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide investigative thought leadership through proactive and strategic contributions (e.g., suggests new analysis, infrastructure or experiments to drive improvements in the business).
- Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of investigative/statistical models, and presentation to stakeholders.
- Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypothesis, and making recommendations from a perspective that combines both, investigative and product-specific expertise.
- Build an understanding of the data sets used by Customer Engagement and its partner teams, and work with Engineering teams to plug gaps in logging and data infrastructure.
- Build data aggregation and analysis pipelines, design new metrics, and create dashboards and visualizations around them.
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