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.
We are the product finance team that supports Google Cloud Platform's (GCP) vast array of products from virtualized compute, big data/analytics, and AI and machine learning tools to its customers at an unparalleled planetary scale and speed.
Our FP&A team supports the product, engineering, and operations teams that build and sell GCP products. We manage the end-to-end cloud product P&L, including revenue, new product development, infrastructure expense, OpEx, and AI capacity. We are an integral partner and strategic financial advisers to the cloud leadership team, advising on how to invest resources to grow a strong and sustainable business.
In this role, you’ll be a member of the AI Solutions Product Finance team. We help to productize and commercialize Gemini and other AI innovations for our Google Cloud customers. You will be the primary finance partner shaping the financial strategy for our AI businesses. You'll act as a trusted advisor on key business and financial decisions related to AI agents and cross-product area collaboration.
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 $171,000-$248,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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
- Develop and maintain sophisticated financial models for AI-related costs and implement chargeback frameworks for internal and external users.
- Partner with product and engineering teams to develop and refine the business models for AI agents, ensuring financial viability and alignment with our strategic goals.
- Be able to advise agent developers on the best avenues to create flexible, resilient products commercialized in the best avenue possible given emerging trends in AI related to business models, infrastructure costs, and capacity planning.
- Provide data-driven insights and strategic financial advice to leadership on investment decisions, resource allocation, and long-term financial planning for our AI businesses.
- Drive high-impact, cross-product area collaboration opportunities, creating financial models to evaluate and support these initiatives.
Qualifications
Minimum qualifications:
- Bachelor's degree in Business, Finance, Economics, Statistics, or another quantitative field, or equivalent practical experience.
- 10 years of experience in financial planning and analysis (FP&A), consulting, or a related function, or an advanced degree.
- Experience executing full-cycle FP&A functions including budgeting, forecasting, variance analysis, and modeling within a multinational company setting.
Preferred qualifications:
- Advanced degree (e.g., MBA, CFA, or other similar qualification).
- Experience in or a strong understanding of the enterprise technology space or emerging AI/agents.
- Experience leading cross-functional project teams through strong problem-framing and problem-structuring skills, and project management skills.
- Expertise with SQL and data visualization tools.
- Ability to communicate insights and reasoning to a wide range of stakeholders including highly technical management teams.