Financial Analyst, Artificial Intelligence/Machine Learning

Minimum Qualifications:

• Bachelor's degree in Business, Finance, Economics, Statistics, or another quantitative field, or equivalent practical experience.
• 4 years of experience in financial planning and analysis, and other related functions, or an advanced degree.
• Experience in an analyst role supporting Financial Analysis, Portfolio Management, Due Diligence, and related functions.
• Experience using SQL for analysis and modeling.

Preferred Qualifications:

• Experience with building data infrastructure (e.g., designing architecture, building data pipelines, implementing scalable monitoring) and implementing reporting solutions.
• Experience with data center hardware technology and data center capacity planning and budgeting.
• Experience in developing strategies in a changing environment.
• Ability to work with data to produce analysis, influencing decision making with numerical analysis and generating insights.
• Ability to communicate insights to technical management teams and align business leaders on recommendations and decisions.
• Excellent project management skills.

About The Job

In this role you will deliver insights to help leaders make decisions on allocating resources effectively. You will also help build alignment across a broad set of stakeholders as we work towards unlocking value for Alphabet.

This role will support Finance, Product, and Technical Program Management teams across all of Google, and will help the mission of Driving Machine Learning (ML) Excellence for Google and the World through as part strategy which is increasing the ease and speed of landing product innovations with ML, delivering scalable ML compute infrastructure, and driving sustained hardware innovation and make it universally accessible and scalable.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 $113,000-$162,000 + 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.
The US base salary range for this full-time position is $113,000-$162,000 + 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

• Engage with product area finance and other central business partner teams to understand ML capacity demand across Google, and collaborate to ensure alignment on Single Source of Truth (SSOT) datasets for reporting.
• Perform (compute and financial) analyses and uplevel insights to ensure investment decisions are in line with Google’s priorities.
• Apply SQL knowledge in data aggregation, synthesization and automation to streamline financial analyses.
• Identify ways to improve the short- and long-term ML allocations process and work cross-functionally to implement changes, while taking into considerations of financial implications; establish monthly/quarter reports on portfolio performance, trends, and Product Area analyses against goals and track the performance of existing Artificial Intelligence/Machine Learning (AI/ML) allocations, identifying any potential issues or areas for rebalancing.
• Support the automated charge back process for Alphabet.