Data Scientist, Research, Ads Insight and Measurement

Google-posted 4 days ago
Full-time • Mid Level
Mountain View, CA
5,001-10,000 employees
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As a Data Scientist, you will apply scientific and statistical methods to the challenges of advertising product creation, development, and improvement, bringing a deep, data-driven appreciation for the behaviors of the end user and the ecosystem. Working within Ads Insights and Measurement, you will develop, evaluate, and improve the entire range of Google's advertising products, including Search, Display, Apps, TV, and Video (YouTube). You will collaborate closely with a multidisciplinary team of engineers, analysts, and product managers to develop new scientific approaches and translate them into deployed products at scale. You will play a key role in developing new ideas and methods that drive ad measurement and business generation, including paradigm-shifting ad-measurement science and products for the privacy-preserving future of digital advertising. In doing so, you will drive impact on ad systems both at Google and in the global ad-tech and mar-tech industries. Equipped with a broad set of technical skills, you will be ready to take on some of modern advertising’s greatest challenges and make an impact on the entire global ads ecosystem. You will be quantitatively trained, with expertise in quantitative methodologies and have an understanding of statistics and causal inference methods. You will understand consumer behavior, advertising, and privacy, possessing a passion for business problems and an interest in combining data and strategy.

  • Support and shape new data-driven and privacy-preserving advertising and marketing products in collaboration with engineering, product and customer facing teams
  • Collaborate with teams to define relevant questions about advertising effectiveness, incrementality assessment, the impact of privacy, user behavior, brand building, targeting, bidding etc.
  • Find ways to combine large-scale experimentation, statistical-econometric, machine learning and social-science methods to answer business questions at scale
  • Use causal inference methods to design and suggest experiments and new ways to establish causality, assess attribution and answer strategic questions using data.
  • Work with large, complex data sets.
  • Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed.
  • Conduct end-to-end analyses that include data gathering and requirements specification, exploratory data analysis (EDA), model development, and written and oral delivery of results to business partners and executives.
  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 3 years of 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.
  • PhD degree in a quantitative discipline.
  • Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data.
  • Ability to both teach others and learn new techniques such as differential privacy, with excellent leadership and self-initiation.
  • Ability to select the right statistical tools to solve a data analysis problem.
  • Excellent communication skills, with a passion for practical application of science to business.
  • bonus
  • equity
  • benefits
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