Financial Crime Prevention Specialist preventing illegal activities like money laundering and fraud. Join a fast - growing fintech company managing compliance in a hybrid or remote role.
About the role
- Quantitative Risk Analyst developing and implementing financial crimes models for USAA. Utilizing advanced analytics to drive risk assessment and model optimization in a collaborative environment.
Responsibilities
- 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.
Requirements
- 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.
- 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 OR PhD in Economics, Finance, Statistics, Mathematics, or other quantitative discipline.
- A Master degree in a quantitative field.
- Advanced knowledge of statistical and machine learning models and techniques.
- 3+ years of experience in developing, validating and implementing Financial Crimes Models.
- Solid understanding of AML and Financial Crimes modeling techniques.
- 8+ 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, preferable modern systems leveraging Machine Learning Algorithm for Detection.
Benefits
- Comprehensive medical, dental and vision plans
- 401(k)
- Pension
- Life insurance
- Parental benefits
- Adoption assistance
- Paid time off program with paid holidays plus 16 paid volunteer hours
- Various wellness programs
- Career path planning and continuing education
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