AdTechTalent
Data Science16 days agoOn-site

Google

Data Scientist, Ads Insight and Measurement

pythonrsqlmachine learningstatistical analysiscausal inferencead measurementdata scienceadvertisinggoogle ads

Key details

Salary

From $147K

Employment type

Part-time

Seniority

Mid-level

Years experience

3-5

Location

Mountain View, United States

Full job description

Data Scientist role focused on developing and improving Google's advertising products across Search, Display, Apps, TV, and Video. Requires a Master's degree in a quantitative field and 3+ years of experience in analytics, coding (Python, R, SQL), and statistical analysis or a PhD. Preferred experience includes 5+ years in analytics, statistical data analysis, machine learning on large datasets, and causal inference methods. Responsibilities include collaborating with cross-functional teams to develop scalable ad measurement products and applying quantitative methods to solve business problems. Salary range $147,000 - $211,000 plus 15% bonus target and equity. Location: Mountain View, California.

What you'll do

  • Develop, evaluate and improve Google's advertising products including Search, Display, Apps, TV and Video (YouTube)
  • Collaborate closely with engineers, analysts and product managers to develop new science and translate it into deployed products at scale
  • Develop new ideas and methods that drive ad measurement and facilitate agreements
  • Build and drive impact on large-scale ad-systems at Google and in the ad-tech and mar-tech industry globally
  • Leverage quantitative methodologies and causal inference methods to solve business problems
  • Work cross-functionally in a science-driven organization

Requirements

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field
  • 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree
  • Experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods
  • Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data
  • Applied experience with machine learning on large datasets
  • Familiarity with causal inference methods such as split-testing, instrumental variables, fixed effects regression, panel data models, regression discontinuity, matching estimators

Tech stack

PythonRSQLmachine learningstatistical analysiscausal inference

Benefits

15% bonus targetequitybenefits as per Google careers page

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