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Business Data Scientist, Ads Finance Quant

California, United States (On-site)

Business Data Scientist, Ads Finance Quant

1 Month ago • 1-2 Years • Data Analyst

About the job

5 skills required for this role

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

unity

python

sql

data-science

forecasting-budgeting

Job Description

Data drives the way we make decisions at Google, and the Ads Product Finance Quant team is tasked with using data to answer some of the biggest questions facing the company during a period of rapid evolution in our industry. As a Business Data Scientist, you will be at the cutting edge of data analysis, using analytical accuracy and statistical methods to mine through data and answer the complex questions facing Search, YouTube, and Ads. 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. Responsibilities: Solve difficult, non-routine analysis problems, applying advanced analytical methods and statistical approaches. Research and use creativity to develop new ways of modeling and unlock actionable insights. Work with some of the largest, most complex datasets at Google. Summarize analysis findings and present to executive audiences. Work cross-functionally with Finance, Engineering, Product, and other data science teams to advance the state of the art of analysis at Google.

Must have:

Bachelor's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
1 year of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Strong analytical and technical abilities to drive data analysis and insights for executive audiences (e.g., SQL, R, dashboard creation, advanced financial modeling, statistics, forecasting), with attention to detail.
Demonstrated willingness to both teach others and constantly learn new analytical techniques, coding frameworks, etc.

Good to have:

2 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Experience solving fast-moving and complex problems, and comfort navigating large data sets and refining ambiguous questions.
Independent and comfortable dealing with ambiguity and strategic pivots.

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Minimum qualifications:

Bachelor's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
1 year of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.

Preferred qualifications:

2 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Experience solving fast-moving and complex problems, and comfort navigating large data sets and refining ambiguous questions.
Strong analytical and technical abilities to drive data analysis and insights for executive audiences (e.g., SQL, R, dashboard creation, advanced financial modeling, statistics, forecasting), with attention to detail.
Demonstrated willingness to both teach others and constantly learn new analytical techniques, coding frameworks, etc.
Independent and comfortable dealing with ambiguity and strategic pivots.

About the job

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 $108,000-$158,000 + 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 .

Responsibilities

Solve difficult, non-routine analysis problems, applying advanced analytical methods and statistical approaches.
Research and use creativity to develop new ways of modeling and unlock actionable insights.
Work with some of the largest, most complex datasets at Google.
Summarize analysis findings and present to executive audiences.
Work cross-functionally with Finance, Engineering, Product, and other data science teams to advance the state of the art of analysis at Google.

View Full Job Description

$108.0K - $158.0K/yr (Outscal est.)

$133.0K/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.