KPMG US
Senior Associate, Financial Crimes, Data Analytics
KPMG US, Fort Lauderdale, Florida, us, 33336
Overview
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Senior Associate, Financial Crimes, Data Analytics
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KPMG US . KPMG Advisory practice is currently our fastest growing practice. We are seeing tremendous client demand, and we do not anticipate that slowing down. In this environment, our professionals must be adaptable and thrive in a collaborative, team-driven culture. At KPMG, our people are our number one priority, with learning and career development opportunities, a world-class training facility and leading market tools to help you grow both professionally and personally. If you’re looking for a firm with a strong team connection where you can be your whole self, have an impact, advance your skills, deepen your experiences, and have flexibility to find new areas of inspiration, consider a career in Advisory. 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 MBA from an accredited college or university 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 and its affiliates and subsidiaries (“KPMG”) are equal opportunity employers. We comply 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, sex, national origin, disability, or any other protected status. No phone calls or agencies please.
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Join to apply for the
Senior Associate, Financial Crimes, Data Analytics
role at
KPMG US . KPMG Advisory practice is currently our fastest growing practice. We are seeing tremendous client demand, and we do not anticipate that slowing down. In this environment, our professionals must be adaptable and thrive in a collaborative, team-driven culture. At KPMG, our people are our number one priority, with learning and career development opportunities, a world-class training facility and leading market tools to help you grow both professionally and personally. If you’re looking for a firm with a strong team connection where you can be your whole self, have an impact, advance your skills, deepen your experiences, and have flexibility to find new areas of inspiration, consider a career in Advisory. 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 MBA from an accredited college or university 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 and its affiliates and subsidiaries (“KPMG”) are equal opportunity employers. We comply 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, sex, national origin, disability, or any other protected status. No phone calls or agencies please.
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