Senior Associate, Financial Crimes Data Analytics

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KPMG Advisory practice is currently our fastest growing practice. We are seeing tremendous client demand, and looking forward we do not anticipate that slowing down. In this ever-changing market environment, our professionals must be adaptable and thrive in a collaborative, team-driven culture. At KPMG, our people are our number one priority. With a wealth of learning and career development opportunities, a world-class training facility and leading market tools, we make sure our people continue to 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 the flexibility and access to constantly find new areas of inspiration and expand your capabilities, then consider a career in Advisory.

KPMG is currently seeking a Senior Associate, Financial Crimes, Data Analyst to join our Advisory Services practice.

• 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

• 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 Masters of Business Administration (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)

KPMG LLP and its affiliates and subsidiaries (“KPMG”) complies with all local/state regulations regarding displaying salary ranges. If required, the ranges displayed below or via the URL below are specifically for those potential hires who will work in the location(s) listed. Any offered salary is determined based on relevant factors such as applicant s skills, job responsibilities, prior relevant experience, certain degrees and certifications and market considerations.

In addition, KPMG is proud to offer a comprehensive, competitive benefits package, with options designed to help you make the best decisions for yourself, your family, and your lifestyle. Available benefits are based on eligibility. Our Total Rewards package includes a variety of 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.

Depending on job classification, standard work hours, and years of service, KPMG provides Personal Time Off per fiscal year. Additionally, each year KPMG publishes a calendar of holidays to be observed during the…