As a Technical Lead on Google’s Advertising Measurement team, you will apply scientific aptitude, excellence, precision, accuracy, expertise, thoroughness and statistical expertise to navigate the complex challenges of a global, privacy-preserving advertising ecosystem. Google is a pioneer in sustaining an open internet through a mutually-reinforcing cycle of ad-planning, optimization, and measurement; in this strategic leadership role, you will be the recognized authority driving that cycle forward.
You will develop, organize, and launch large-scale projects spanning engineering and analysis across Search, Display, YouTube, and beyond. By translating advanced science specifically causal inference and quantitative methodologies into deployed products, you will lead the charge in defining paradigm-shifting measurement standards for the future of digital advertising. Working cross-functionally with Engineers, Product Managers, and Sales, you will adjust global strategies based on your findings, ensuring advertising remains useful for users and results-driven for publishers. We are seeking quantitatively trained experts with a passion for business strategy and a deep appreciation for consumer behavior.
In this role, you won’t just improve products; you will empower an exceptional team to shape the marketing-technology industry globally. If you thrive in fluid, science-driven environments and are ready to leverage data and technology to solve modern advertising’s greatest challenges, your leadership will be the catalyst for the next era of innovation.
Responsibilities
- Apply causal inference and differential privacy methods to design experiments, assess attribution, and develop privacy-preserving marketing products.
- Execute end-to-end analyses including data gathering, EDA, and model development to deliver strategic insights to executives.
- Build iterative analysis pipelines and prototype data structures to provide scalable insights across Google’s complex data ecosystems.
- Collaborate with Product and Engineering team to define and answer quantitative questions regarding incrementality, user behavior, and bidding optimization.
- Provide technical guidance and prioritization for the team, conduct cost-benefit analyses to drive high-level business decisions and product strategy.
Qualifications
Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or 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.
- Experience with statistical data analysis such as linear models, multivariate analysis, causal inference, or sampling methods.
- Experience with statistical software (e.g., SQL, R, Python, MATLAB, pandas) and database languages along with statistical analysis, modeling and inference.
Preferred qualifications:
- PhD in a quantitative field.
- 10 years of experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods.
- 5 years of leadership experience, including people management.
- Experience with Machine Learning (ML) on large datasets, with the ability to select the right statistical tools in a given data analysis problem.
- Understanding of potential outcomes framework and with causal inference methods such as split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators, with knowledge of structural econometric methods.
- Ability to set and drive technical strategy.