Senior Economist, Economic Impact Estimation
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
MINIMUM QUALIFICATIONS:
- Master's degree in Economics, a related field (e.g., Statistics, Data Science, Public Policy, Business, Finance), or equivalent practical experience.
- 4 years of experience undertaking empirical analysis to solve product, business, or policy problems, with a focus on econometric or statistical modeling.
- Experience in big data analysis, including statistical/econometric software (e.g., R, Python, Stata) and data query languages (e.g., SQL) to manage datasets.
PREFERRED QUALIFICATIONS:
- PhD in Economics, a related field (e.g., Statistics, Data Science, Public Policy, Business Finance), or equivalent practical experience.
- 6 years of experience undertaking empirical analysis including investigating questions of economic impact measurement, ideally within the context of big technology companies or digital platforms.
- Experience in causal inference methodologies and quasi-experimental designs.
- Experience with AI impact analysis.
- Experience in time series forecasting and macroeconomics.
ABOUT THE JOB:
The Google Economics Team provides actionable economic insights and tools to inform strategy and decision-making across Alphabet, and it engages externally on some of the most important policy questions of the moment. Within the team, our Macroeconomics and Economic Impact Reporting area decodes the macroeconomic environment in which Google operates and evaluates the economic and societal impacts of our businesses and investments globally.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
In this role, you will be designing and executing economic impact studies that leverage big data to quantify and clearly communicate Google’s contributions to the macro economy. You will be instrumental in combining advanced econometrics and statistical modeling with large, real-world datasets to produce insights. You will also have the opportunity to support the team’s broader analytical work, including on macroeconomic monitoring and topical issues.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google [https://www.google.com/about/careers/applications/benefits/]
Get help with your application
Your very own career expert that helps elevate your application to the next level.
RESPONSIBILITIES:
- Design and implement economic impact studies, employing economic methodologies to accurately measure Google’s economic impact across regional and global economies.
- Conduct quantitative analyses using advanced econometrics techniques and statistical models. This includes using big data analytical tools and platforms to process, model and measure the economic impact of Google’s activities, programs and products across various sectors, including the economic impact of AI.
- Apply high-level proficiency in data manipulation, cleaning, and transformation of large, unstructured and complex datasets. Ensure data quality and integrity throughout the modeling process.
- Contribute to our monitoring of the wider macroeconomic environment and deliver incisive analysis on key topical issues.
- Translate highly technical findings into compelling, clear, and impactful reports, publications and presentations for audiences, including executives, policymakers, external economists and the general public.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location