Causal Economist, Finance

Key Skills

C++, Design, Econometrics, Python Programming

Job Description

Minimum qualifications:

• PhD in Economics, Operations Research, Management Science, a related field or equivalent practical experience.
• Experience in Programming with R or Python.
• Experience in econometrics and causal inference.

Preferred qualifications:

• Experience in the tech sector, consulting, or public policy.
• Experience with modern causal inference tools and concepts such as synthetic controls and other panel data techniques, doubly robust estimators, and heterogeneous treatment effect estimators.
• Experience designing and analyzing randomized controlled trials.
• Experience designing and analyzing causal studies using observational data.

About the job

As an economist on the Chief Economist’s Team, you will be an internal consultant tasked with helping Google make better decisions. You will be working with many teams such as finance, product, engineering, business, marketing, legal, policy, and research. Your job will be to help decision-makers at Google make informed choices using causal inference. To succeed, you will need excellent communication skills in addition to technical expertise. This means translating vague questions into concrete problems on which you will design studies, and communicating findings to non-technical audiences while being transparent about uncertainty and the assumptions used in your analysis.

Given the nature of the position, you will be encouraged to develop new econometric techniques in collaboration with your teammates and work with our summer interns on research projects. You will also attend relevant conferences and organize internal events to keep our toolkit updated and to educate the broader Google community.

The name Google came from googol, a mathematical term for the number 1 followed by 100 zeros. And nobody at Google loves big numbers like the Finance team when providing in depth analysis on all manner of strategic decisions across Google products. From developing forward-thinking analysis to generating management reports to scaling our automated financial processes, the Finance organization is an important partner and advisor to the business.

The US base salary range for this full-time position is $124,000-$182,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Design and lead causal studies to answer critical business questions.
• Effectively present and communicate actionable insights and recommendations to executives, leaders, and cross-functional partners.
• Serve as a peer-reviewer and consultant for causal studies designed by other teams.
• Stay up to date with advances in the causal inference literature, and develop new methods and tools when appropriate.