Utilizes advanced analytics to assess future risk, opportunities, and effectiveness and translates results into meaningful solutions to enhance decision making.
Applies advanced knowledge and industry best practices to quantify risk and aggregate exposures.
Engages in model validation and produces model validation reports.
Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make recommendations to answer business objectives and drive change.
Translates recommendations into communication materials to effectively present to colleagues for peer review and management.
Applies advanced knowledge to produce advanced analytical material for discussions with cross functional teams to understand complex business objectives and influence solution strategies.
Provides mentorship to other team members in the peer review process.

Bachelor's degree in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, or other quantitative discipline or 4 additional years of related experience beyond the minimum required may be substituted in lieu of a degree.
6 years related quantitative analysis experience in a discipline relevant to risk management to include statistical analysis, modeling, mathematics or other quantitative discipline OR advanced degree/designation in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, or other quantitative discipline and 4 years work experience in a quantitative discipline relevant to risk management OR PhD in Economics, Finance, Statistics, Mathematics, or other quantitative discipline and up to 2 years work experience in a quantitative discipline relevant to risk management.
A Master or Ph.D. degree in a quantitative field.
Advanced knowledge of statistical and machine learning models and techniques.
5+ years of experience in developing, validating and implementing Financial Crimes Models.
Solid understanding of AML and Financial Crimes modeling techniques.
10+ years of hands-on technical coding experience and strong programming skills, e.g. Python, SAS, SQL, R.
Prior experience working on Transaction Monitoring Platform such as Actimize, Lexis Bridger, preferrable modern systems leveraging Machine Learning Algorithm for Detection.

Senior Quantitative Risk Analyst – AML Modeling

Key skills