Minimum qualifications:
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Preferred qualifications:
- 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
- Experience using Generative AI to transform corporate processes.
- Ability to track record of dealing well with ambiguity and delivering quantifiable results in an environment.
- Excellent communication (written and verbal) to translate technical solutions and methodologies to senior leadership.
At Google, data drives all of our decision-making. As part of the Finance Data and Analytics (DnA) team, you will use data to inform business, process and product decisions across Google. In this role, you will have the opportunity to incubate AI solutions at scale at Google’s Finance Center of Excellence. You will partner with business and finance teams across different product areas and functions to drive process efficiency and performance management insights. The team works on ML, AI and Agentic solutions.The US base salary range for this full-time position is $197,000-$291,000 + 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.
- Work cross-functionally with analysts, engineers, and program managers to develop and deploy AI/ML solutions.
- Use a product-driven mindset to transform key Finance processes through AI/ML.
- Communicate results to peers, stakeholders and leaders.
- Explore the Art of the Possible in Finance with Rapid AI Prototyping.
- Coach junior members and share knowledge with the broader team.
