KPMG US
Senior Associate, Financial Crimes, Data Analytics
KPMG US, Detroit, Michigan, United States, 48228
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Senior Associate, Financial Crimes, Data Analytics
role at
KPMG US .
KPMG is currently seeking a Senior Associate, Financial Crimes, Data Analyst to join our Advisory Services practice.
Responsibilities
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.
Qualifications
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 is required, with preference given to data science, computer science, statistics, math or related quantitative field of study, or an MBA from an accredited institution.
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 now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H‑1B, L‑1, TN, O‑1, E‑3, H‑1B1, F‑1, J‑1, OPT, CPT or any other employment-based visa).
KPMG offers a comprehensive compensation and benefits package.
KPMG is an equal opportunity employer. KPMG complies with all applicable federal, state, and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state, and local laws. The attached link contains further information regarding KPMG's compliance with federal, state and local recruitment and hiring laws. No phone calls or agencies please.
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Senior Associate, Financial Crimes, Data Analytics
role at
KPMG US .
KPMG is currently seeking a Senior Associate, Financial Crimes, Data Analyst to join our Advisory Services practice.
Responsibilities
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.
Qualifications
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 is required, with preference given to data science, computer science, statistics, math or related quantitative field of study, or an MBA from an accredited institution.
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 now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H‑1B, L‑1, TN, O‑1, E‑3, H‑1B1, F‑1, J‑1, OPT, CPT or any other employment-based visa).
KPMG offers a comprehensive compensation and benefits package.
KPMG is an equal opportunity employer. KPMG complies with all applicable federal, state, and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state, and local laws. The attached link contains further information regarding KPMG's compliance with federal, state and local recruitment and hiring laws. No phone calls or agencies please.
#J-18808-Ljbffr