KPMG US
Senior Associate, Financial Crimes Data Analytics
KPMG US, Detroit, Michigan, United States, 48228
Senior Associate, Financial Crimes Data Analytics – KPMG US
We are looking for a Senior Associate with expertise in financial crime and data analytics to join our Advisory Services practice.
Responsibilities
Develop, calibrate, and validate statistical, machine learning, and artificial intelligence models to detect and prevent financial crimes (fraud, money laundering, sanctions violations).
Assess and monitor model performance 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 for 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.
Qualifications
Minimum three years’ recent experience in quantitative analysis for financial crime detection, using advanced statistical methods.
Bachelor’s degree in data science, computer science, statistics, mathematics, or related field; MBA preferred.
Proficient in SQL, Python, SAS, and R, and experienced with Tableau or Power BI.
Excellent communication and report‑writing skills.
Ability to translate complex data insights into actionable recommendations.
Experience applying machine learning or AI techniques within financial crime risk management.
Must be authorized to work in the U.S. without future visa sponsorship.
KPMG is an equal‑opportunity employer. All qualified applicants, regardless of race, color, religion, age, gender identity, sexual orientation, or protected veteran status, are considered for employment without attribution to any class protected by federal, state, or local law. This opportunity is open to those who are legally authorized to work in the U.S. without sponsorship.
Benefits include medical, dental, vision, disability, life insurance, 401(k) plans, and personal well‑being programs. Additional information about the Total Rewards package is available on the KPMG US Careers site.
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Responsibilities
Develop, calibrate, and validate statistical, machine learning, and artificial intelligence models to detect and prevent financial crimes (fraud, money laundering, sanctions violations).
Assess and monitor model performance 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 for 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.
Qualifications
Minimum three years’ recent experience in quantitative analysis for financial crime detection, using advanced statistical methods.
Bachelor’s degree in data science, computer science, statistics, mathematics, or related field; MBA preferred.
Proficient in SQL, Python, SAS, and R, and experienced with Tableau or Power BI.
Excellent communication and report‑writing skills.
Ability to translate complex data insights into actionable recommendations.
Experience applying machine learning or AI techniques within financial crime risk management.
Must be authorized to work in the U.S. without future visa sponsorship.
KPMG is an equal‑opportunity employer. All qualified applicants, regardless of race, color, religion, age, gender identity, sexual orientation, or protected veteran status, are considered for employment without attribution to any class protected by federal, state, or local law. This opportunity is open to those who are legally authorized to work in the U.S. without sponsorship.
Benefits include medical, dental, vision, disability, life insurance, 401(k) plans, and personal well‑being programs. Additional information about the Total Rewards package is available on the KPMG US Careers site.
#J-18808-Ljbffr