As a part of the Google Payments Compliance team, you will work to safeguard Google's users and protect products from fraud and financial crimes abuse by ensuring strict adherence to global Anti-Money Laundering (
AML)/Counter-Terrorist Financing (
CTF) regulations. You will partner with Regional Compliance, Payments Platform, and Engineering teams to manage financial crime risk across Google's entire payments ecosystem. You will be responsible for designing, implementing, and optimizing the
AML program, processes, and operations that ensure Google maintains regulatory compliance.
In this role, you will be responsible for supporting the global development and strategic management of Google Payments' systemic
AML/
CTF transaction monitoring program. You will also focus on building reporting dashboards, automating operational workflows, and assisting in the tuning and governance of monitoring triggers (rules and models). Additionally, you will support initiatives to integrate AI capabilities into operational workflows to drive efficiency, accuracy, and scalability across compliance operations.The US base salary range for this full-time position is $108,000-$153,000 + 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
- Collaborate with the Transaction Monitoring Lead to develop, test, and deploy static rules and machine learning models that enhance AML detection.
- Maintain comprehensive documentation of monitoring logic, risk coverage, and tuning processes.
- Design AI agents and refine Large Language Model (LLM) prompts to accurately identify and classify financial crime patterns.
- Build visualization dashboards and automated workflows to report on performance and reduce manual tasks.
- Execute ad-hoc data queries and quantitative analysis to support technical projects and emerging risk scenarios.
Minimum qualifications:
- Bachelor's degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Mathematics, Information Systems) or equivalent practical experience.
- 1 year of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
- 1 year of experience in an analytical, data science, or quantitative risk management role within AML compliance, trust and safety, or financial services.
Preferred qualifications:
- Master's degree in a quantitative discipline.
- Experience writing and optimizing SQL queries to extract, clean, and analyze datasets.
- Experience building data visualizations or dashboards (e.g., Tableau, Looker, Business Intelligence Platform, or equivalent) and automating workflows (e.g., using Python, scripting, or basic automation tools).
- Excellent written and verbal communication skills.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Chicago, IL, USA; Austin, TX, USA.