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.
- 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.
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About the job
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.
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 benefits at Google .
Responsibilities
- Solve difficult, non-routine analysisproblems, 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 thelargest, 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.