KPMG US
Senior Associate, Financial Crimes, Quantitative Analytics
KPMG US, Stamford, Connecticut, United States, 06925
Overview
Senior Associate, Financial Crimes Analytics role within KPMG US Advisory Services. This position focuses on developing, calibrating, and applying quantitative methods to detect and prevent financial crimes, including fraud, money laundering, and sanctions violations. 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 Provide quantitative support for risk assessments, regulatory reporting, and periodic audits related to financial crimes Contribute to the design and implementation of data quality, governance, and model risk management frameworks Qualifications
Three years of specialized experience in 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, statistics, math or related quantitative field of study; MBA is preferred Proficient in programming languages such as Python 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 Skilled in risk assessment, data-driven decision making, and extracting actionable insights from complex datasets 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 KPMG LLP and its affiliates and subsidiaries (“KPMG”) complies with all local/state regulations regarding displaying salary ranges. If required, ranges are for those potential hires in the listed locations. Any offered salary is determined based on relevant factors such as skills, experience, degrees, and market considerations. KPMG offers a comprehensive compensation and benefits package and is an equal opportunity employer. All qualified applicants will be considered without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, or any other category protected by applicable laws. No phone calls or agencies please. Recruitment is on a rolling basis. Los Angeles County applicants: material job duties are listed above. We will consider qualified applicants with arrest or conviction records in accordance with applicable laws.
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Senior Associate, Financial Crimes Analytics role within KPMG US Advisory Services. This position focuses on developing, calibrating, and applying quantitative methods to detect and prevent financial crimes, including fraud, money laundering, and sanctions violations. 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 Provide quantitative support for risk assessments, regulatory reporting, and periodic audits related to financial crimes Contribute to the design and implementation of data quality, governance, and model risk management frameworks Qualifications
Three years of specialized experience in 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, statistics, math or related quantitative field of study; MBA is preferred Proficient in programming languages such as Python 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 Skilled in risk assessment, data-driven decision making, and extracting actionable insights from complex datasets 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 KPMG LLP and its affiliates and subsidiaries (“KPMG”) complies with all local/state regulations regarding displaying salary ranges. If required, ranges are for those potential hires in the listed locations. Any offered salary is determined based on relevant factors such as skills, experience, degrees, and market considerations. KPMG offers a comprehensive compensation and benefits package and is an equal opportunity employer. All qualified applicants will be considered without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, or any other category protected by applicable laws. No phone calls or agencies please. Recruitment is on a rolling basis. Los Angeles County applicants: material job duties are listed above. We will consider qualified applicants with arrest or conviction records in accordance with applicable laws.
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