Staff Data Scientist Manager, Ads Metrics

1 Day ago • 8-10 Years • Data Analyst • $197,000 PA - $291,000 PA

Job Summary

Job Description

The Staff Data Scientist Manager, Ads Metrics at Google will collaborate with stakeholders to translate business questions into analytical solutions. This role requires designing and evaluating mathematical models, gathering and cleaning data using tools like SQL, R, and Python, and leading GenAI exploration within Ads Metrics. The ideal candidate will have 8+ years of experience in analytics, coding, and database querying, along with 5+ years of experience with AI/ML technologies in media and entertainment. Three years of people management experience in a technical leadership role is also required. Responsibilities include identifying business questions, refining analysis methods, using custom or existing data models, gathering data, and ensuring data quality for analysis.
Must have:
  • Master's degree in quantitative field or equivalent experience
  • 8+ years analytics experience solving business problems
  • 5+ years experience with AI/ML in media and entertainment
  • 3+ years people management experience
  • Proficiency in Python, R, SQL
Good to have:
  • 10+ years of experience in analytics
  • PhD degree
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

Minimum qualifications:

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
  • 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
  • 5 years of experience with analytics and AI/ML technologies, including their current and potential applications to the media and entertainment industry.
  • 3 years of experience as a people manager within a technical leadership role.
  • Experience working with consumer-facing tech products.

Preferred qualifications:

  • 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

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.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

  • Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
  • Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
  • Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
  • Lead Ads Metrics' GenAI exploration.

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