Quantitative Risk Analyst (Mid-level) - AML Modeling

Utilizes advanced analytics to assess future risk, opportunities, and effectiveness and translates results into meaningful solutions to enhance decision making.

Assesses and mitigates exposures through the identification of key and emerging risks in alignment with the risk strategy and appetite.

Applies knowledge to produce analytical material for discussions with cross functional teams to understand complex business objectives and influence solution strategies.

Produces and communicates analytical content for discussions with cross functional teams, governance committees and business process owners to influence business strategies.

May create statistical reporting and financial analysis to forecast results for required stress test scenarios, including analyzing and challenging stress testing results and partnering with relevant functions to validate those results.

May engage in model validations, produce model validation reports, measure and aggregate model risks, and/or report on model issues to committees, auditors, and regulators.

Bachelor's degree in Economics, Finance, Statistics, Mathematics, Engineering, Actuarial Sciences, or quantitative field; OR 4 years of relevant education and/or experience.

Experiences that will support your success:

4 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 2 years work experience in a quantitative discipline relevant to risk management.

US military experience gained through military service or gained as a military spouse / domestic partner

Bachelor's or Master's degree in Statistics, Mathematics, Economics, Finance, Data Science, or a related quantitative field.

4+ years of quantitative risk, model risk, fraud risk, or analytics experience within a large financial institution.

2+ years of AML-focused experience, including transaction monitoring, customer risk scoring, sanctions, financial crimes analytics, or AML model development/validation.

Proficiency in SQL, Python, SAS, R, or similar analytical tools.

Knowledge of AML regulations, model governance, and risk management frameworks.

Strong problem-solving abilities with exceptional attention to accuracy and detail.