Research Data Scientist, Ads Insights
About the role
MINIMUM QUALIFICATIONS:
- 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.
PREFERRED QUALIFICATIONS:
- 5 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.
ABOUT THE JOB:
Google’s advertising measurement team focuses on combining data at scale with
formal science to make this possible. Our science helps make advertising useful
and delightful to our users, and valuable and results-driven for our advertisers
and publishers.
As a Data Scientist working on Ads Insights, you will play a key role in
developing new ideas and methods that drive business generation, including
paradigm-shifting products for the privacy-preserving future of digital
advertising. In doing so, you will be a key part of building and driving impact
on large-scale ad systems both at Google and in the ad-tech and mar-tech
industry as a whole, globally.
Individual pay is determined by factors including job-related skills,
experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].
RESPONSIBILITIES:
- Help suggest, guide, 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., and develop and implement
quantitative methods to answer those questions.
- 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 questions using data.
- Build and prototype analysis pipelines iteratively to provide insights at
scale, and develop comprehensive knowledge of Google data structures and
metrics, advocating for changes where needed for product development.
Responsibilities
- Shape privacy-preserving advertising and marketing products with engineering, product, and customer-facing teams.
- Define advertising effectiveness questions and develop quantitative methods to answer them.
- Combine experimentation, statistical-econometric, machine learning, and social-science methods to address business questions at scale.
- Use causal inference to design experiments, assess attribution, and establish causality.
- Build analysis pipelines and develop knowledge of Google data structures and metrics.
Qualifications
- Master's degree in a quantitative field or a PhD degree.
- At least 3 years of experience using analytics, coding, database querying, or statistical analysis to solve product or business problems.
- Preferred: 5 years of relevant experience.
Benefits
- 15% target bonus
- Equity
- Benefits
Skills mentioned
About Google
A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone. Check out our career opportunities at goo.gle/3DLEokh
H-1B sponsorship history
Historical employer filing data was found for Google. The employer record includes 57,181 historical certified applications. This is employer-level history, not a guarantee that this role currently offers sponsorship.