Senior Business Intelligence Analyst I, Finance

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. Working on multiple projects at a time, you are focused on the details while finding creative ways to take on big picture challenges.

As someone who knows the workings of the core Finance team inside and out, you'll lead individual projects to transform planning, tracking and control processes. You'll provide senior level management with insightful recommendations, planning and reporting support.

As a Senior Financial Analyst, the role is a position at the nexus of finance, data strategy, and technological innovation. You will be an expert in financial modeling conducting advanced analysis to quantify the impact of major business, engaged, and regulatory decisions, directly shaping executive strategy. A key focus is data leadership: you will project manage the rollout and adoption of our new core finance data platform and develop expertise in granular user and performance data. Furthermore, you will serve as the team's AI expert, pioneering the development and implementation of new AI-based tools to automate processes, enhance forecasting, and drive efficiency. You will be an investigative, project-oriented professional eager to lead change and translate data into actionable executive insights.

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 $141,000-$207,000 + 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

• Conduct advanced financial modeling and scenario analysis to assess the financial impact of business decisions, engaged changes, and evolving regulatory environments.
• Serve as the Financial Planning and Analysis (FP&A) team's primary technical lead and project manager for the launch, testing, and adoption of our new core finance data platform.
• Develop and apply expertise in non-traditional financial datasets, such as granular user and product performance metrics, to enhance the depth and insight of financial analysis.
• Pioneer and advocate the use of Artificial Intelligence within the team by developing and deploying new AI-based tools and approaches to automate workflows and improve forecasting accuracy.
• Translate quantitative analysis and data findings into clear, actionable financial insights for executive leadership to enable swift, high-stakes decision-making.

Minimum qualifications:

• Bachelor's degree in a quantitative discipline or equivalent practical experience.
  
• 6 years of experience in business intelligence, analytics, financial modeling, and quantitative analysis related fields.
• Experience in Programming and SQL.
  

Preferred qualifications:

• Master's degree in a quantitative discipline.
• Experience with Python or a similar object oriented programming language and with visualization tools (e.g., Tableau, Power BI, Looker, etc.).
• Understanding of data disciplines, finance processes and terminologies and familiarity with Machine Learning (ML) concepts and terminology.
• Ability to work with various stakeholders (e.g., Engineering, Data Science) and translate business objectives into actionable analyses and to work in a changing environment with a tolerance for ambiguity.
• Proficiency with one or more statistical software packages (i.e., R).
• Excellent technical skills and advanced spreadsheet skills.