KPMG US
Senior Associate, Financial Crimes, Data Analytics
KPMG US, Rochester, New York, United States
Senior Associate, Financial Crimes, Data Analytics
KPMG US Advisory Services is seeking a Senior Associate to develop and validate statistical, machine learning, and artificial intelligence models used 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.
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 a 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 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).
Benefits KPMG offers a comprehensive, competitive benefits package, including medical and dental plans, vision coverage, disability and life insurance, 401(k) plans, and a robust suite of personal well-being benefits to support your mental health. Eligible employees receive Personal Time Off, and the company publishes a calendar of holidays and additional benefit details are available on the KPMG US Careers site.
Equal Opportunity Employer 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. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring.
#J-18808-Ljbffr
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 a 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 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).
Benefits KPMG offers a comprehensive, competitive benefits package, including medical and dental plans, vision coverage, disability and life insurance, 401(k) plans, and a robust suite of personal well-being benefits to support your mental health. Eligible employees receive Personal Time Off, and the company publishes a calendar of holidays and additional benefit details are available on the KPMG US Careers site.
Equal Opportunity Employer 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. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring.
#J-18808-Ljbffr