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Senior Associate, Financial Crimes, Data Analytics
Senior Associate, Financial Crimes, Data AnalyticsKPMG US • Short Hills, NJ, US
Senior Associate, Financial Crimes, Data Analytics

Senior Associate, Financial Crimes, Data Analytics

KPMG US • Short Hills, NJ, US
13 hours ago
Job type
  • Full-time
Job description

Join to apply for the Senior Associate, Financial Crimes, Quantitative Analytics role at KPMG US

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, Quantitative 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
  • 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

  • Minimum three years of recent experience specialized 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; Masters of Business Administration (MBA) from an accredited college or university 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
  • Additional information

    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. 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. Details about benefits are available on the KPMG US Careers site.

    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, or local laws.

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    Senior Associate Financial • Short Hills, NJ, US

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