Data Scientist Manager II, Product, AViD Buyside
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Minimum qualifications:
- Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
- 7 years of experience with statistical data analysis.
- 5 years of experience with data mining, querying, and managing analytical projects.
- 3 years of experience developing and managing metrics or evaluating programs/products.
- 3 years of experience as a people manager within a technical leadership role.
Preferred qualifications:
- 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- 4 years of experience as a people manager within a technical leadership role.
- Experience in Ads-Tech, Market Research, or Advertising Analytics.
About the job
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
Responsibilities
- Lead the Data Science team supporting the Product and Engineering organization and contribute to the Ads business strategy through analysis of marketing trends, and product opportunity sizing.
- Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide thought leadership through proactive and strategic contributions (e.g., suggests new analyses, 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 statistical models, and presentation to stakeholders.
- Develop solutions, lead and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines investigative and product-specific expertise.
- Oversee the integration of project/process timelines, and help define operational goals and objectives.
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