Senior Associate, Financial Crimes Data Analytics

Senior Associate, Financial Crimes Data Analytics

Join KPMG US Advisory practice as a Senior Associate in Financial Crimes Data Analytics.

• Develop, calibrate, and validate statistical, machine learning, and artificial intelligence models used to detect and prevent financial crimes, including fraud, money laundering, and sanctions violations.
• Assess and monitor the performance of quantitative models through back testing, benchmarking, and statistical analysis.
• Analyze large and complex datasets to uncover patterns, anomalies, and trends indicative of illicit financial activities.
• Perform analysis to carry out BSA/AML risk assessments, model valuations, and audits related to financial crimes.
• Contribute to the design and implementation of data quality, governance, and model risk management frameworks.

• Minimum three years of recent experience performing quantitative analysis for financial crime detection, leveraging advanced statistical methods and data modeling techniques.
• Bachelor’s degree from an accredited college or university in data science, computer science, statistics, mathematics, or a related quantitative field is required; an MBA is preferred.
• Proficient in programming languages such as SQL, Python, SAS, and R to build, validate, and implement models for transaction monitoring, anomaly detection, and fraud analytics; experienced with data visualization tools such as Tableau or Power BI.
• Excellent communication and report‑writing skills.
• Ability to analyze complex datasets and communicate actionable insights to diverse audiences.
• Experience applying machine learning or artificial intelligence techniques within financial crime risk management.
• Must be authorized to work in the U.S. without the need for employment‑based visa sponsorship.

KPMG offers a comprehensive benefits package that includes medical, dental, vision, life insurance, a 401(k) plan, and a range of well‑being benefits.

KPMG is an equal‑opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, national origin, disability, veteran status, or any other protected category.