Minimum qualifications:
- Bachelor's degree in a quantitative or financial discipline or equivalent practical experience.
- 7 years of experience in financial planning and analysis (FP&A), consulting, or a related function, or an advanced degree.
- 5 years of experience working with spreadsheets.
- 3 years of experience working with SQL.
- MBA or Master's degree in Advanced Analytics or Data Science.
- 6 years of experience influencing and guiding large projects and decisions.
- 2 years of experience in Data Center Operations or finance support.
- Experience in cross-functional collaboration.
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About the job
Financial Analysts ensure that Google makes sound financial decisions. As a Financial Analyst, your work, whether it's modeling business scenarios or tracking performance metrics, is used by our leaders to make strategic company decisions. While working on multiple projects at a time, you are focused on the details while finding creative ways to solve big picture challenges.
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
- Collaborate with cross-functional leaders, apply analysis and foster strong partnerships to forecast, plan, and guide strategic data center expansion.
- Collaborate with cross-functional stakeholders in Go-To-Market (GTM), Capacity Planning, ML teams, etc. to gather all the needed pieces for Power LRP cycles.
- Partner with Capacity Planning to understand Business and Power relationships and influence changes to our metro level power plan.
- Collaborate with various teams to align long-term ML strategy to data center deployment and ensure the latest business signal is used in Power LRP for downstream purposes. Collaborate with Operations Data Science to develop ML-based statistical approaches to assist in forecasting efforts.
- Work with TI Finance to understand CapEx and OpEx response to power signal and advise leadership on opportunities for efficiencies.