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Business Data Scientist, Economist

California, United States (On-site)

Business Data Scientist, Economist

1 Month ago • 3 Years +

About the job

5 skills required for this role

Test your skills to join the top 1% applicants for this job

python

sql

data-science

communication

cross-functional

Job Description

As a Business Data Scientist, Economist at Google, you'll be an internal consultant using causal inference to guide Google's decision-making across various teams like Finance, Product, Engineering, Business, Marketing, Legal, Policy, and Research. You'll translate vague questions into concrete problems, design studies, and effectively communicate findings to non-technical audiences, highlighting uncertainty and assumptions. You'll be working with modern methods in causal inference and Machine Learning (ML), developing new techniques and models when needed. This role requires strong communication skills alongside technical expertise, making you a valuable asset to Google's decision-making process.

Must have:

Master's degree in Economics, Operations Research, Management Science, Statistics or related fields
3 years of experience in programming with R, Python, or SQL
Experience in causal inference, applied statistics, applied microeconomics or econometrics
Excellent communication skills

Good to have:

PhD in Economics, Operations Research, Management Science, Statistics, or in a related technical field
Experience working or prior internships in tech, public policy, data science, or economic consulting
Experience with modern causal inference, statistical tools and concepts
Experience with synthetic controls and other panel data techniques, doubly robust estimators, and heterogeneous treatment effect estimators
Experience designing and analyzing randomized controlled trials or observational studies

Perks:

bonus
equity
benefits

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Minimum qualifications:

Master's degree in Economics, Operations Research, Management Science, Statistics or related fields, or equivalent practical experience.
3 years of experience in programming with R, Python, or SQL as demonstrated by projects, coursework or a public portfolio.
Experience in causal inference, applied statistics, applied microeconomics or econometrics demonstrated by projects, coursework, or publications.

Preferred qualifications:

PhD in Economics, Operations Research, Management Science, Statistics, or in a related technical field.
Experience working or prior internships in tech, public policy, data science, or economic consulting.
Experience with modern causal inference, statistical tools and concepts demonstrated in past projects, coursework, or publications.
Experience with synthetic controls and other panel data techniques, doubly robust estimators, and heterogeneous treatment effect estimators.
Experience designing and analyzing randomized controlled trials or observational studies, demonstrated in past projects, coursework, or publications.
Experience in causal inference, applied microeconomics, or econometrics demonstrated in projects, coursework, or publications.

About the job

In this role, you will be an internal consultant tasked with helping Google make better decisions through the use of causal inference. 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 econometric and statistical methods. You will have excellent communication skills in addition to technical expertise. You will translate vague questions into concrete problems on which you can design studies, and communicate findings to non-technical audiences while effectively conveying uncertainty and the assumptions used in your analysis.

You will have experience with modern methods in causal inference and Machine Learning (ML). Google uses a large set of tools from experimental to observational techniques, touching on a broad range of problems from different functional and product areas. When available methodologies are not well-suited for the problem you are trying to solve, you will need to develop new techniques and models.

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 $127,000-$187,000 + 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 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 .

Responsibilities

Design and lead causal inference studies to answer critical business questions and evaluate effects of interventions.
Present and communicate actionable insights and recommendations to executives, leaders, and cross-functional partners.
Serve as a subject matter expert, reviewer and consultant for causal inference studies conducted by cross-functional teams.
Develop and maintain internal tools and statistical software packages for investigative tasks and impact measurement.

View Full Job Description

$127.0K - $187.0K/yr (Outscal est.)

$157.0K/yr avg.

Mountain View, California, United States

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About The Company

Google

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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.