United Services Automobile Association (USAA)
Quantitative Risk Analyst Lead-AML ModelingPosted
4 weeks ago
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Job Description
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Why USAA?
Let's do something that really matters.
At USAA, we have an important mission: facilitating the financial security of millions of U.S. military members and their families. Not all of our employees served in our nation's military, but we all share in the mission to give back to those who did. We're working as one to build a great experience and make a real impact for our members.
We believe in our core values of honesty, integrity, loyalty and service. They're what guides everything we do - from how we treat our members to how we treat each other. Come be a part of what makes us so special!
USAA AML Modeling & Analytical Team seeks a dedicated Quantitative Risk Analyst Lead to lead a team of Senior and Junior Quantitative Risk Analysts to build, enhance and implement a suite of Financial Crimes Models including Transaction Monitoring (Actimize)and Customer Risk Scoring Model. This role will apply expert analytical capability and deep technical experience to design and improve model performance for AML Transaction Monitoring and Customer Risk Score Model. This role will work with leadership to remediate gaps and improvements identified between existing practices and regulatory requirements. This role will lead and implement complex initiatives and cross functional teams and across the Enterprise that drive problem resolution.
This position can work remotely in the continental U.S. with occasional business travel.
The Opportunity
What you'll do:
* Lead a team of quantitative analysts to develop, enhance and implement a suite of quantitative models used to detect potential suspicious criminal activities for all the products and lines of business in which USAA operates.
* Apply expert analytical knowledge and use advanced analytics to assess future risk and/or new risks. Develop new methodology to identify weak spots in AML Transaction Monitoring Models and promote advanced analytics (i.e. Machine Learning ) algorithm to modernize Financial Crimes Detection Models.
* Enhance USAA transaction monitoring models through periodical model enhancement activities including ongoing threshold tuning, calibration and model optimization.
* Develop effective working relationship with partners at all tiers. Effectively work with business financial crime leaders to understand their needs and deliver analytical solutions
* Interact and partner with Model Risk Management functions to ensure appropriate model risk subject area, requirements and governance is employed again all AML models.
* Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make recommendations to answer business objectives and inspire change.
* Facilitate technical & quantitative skill-building within the team including training, research and innovation. Provides direction and mentorship to other team members.
What you have:
* Bachelor's degree in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, or other quantitative subject area and 4 additional years of related experience beyond the minimum required may be substituted in lieu of a degree.
* 8 years of related quantitative analysis experience in a subject area relevant to risk management to include statistical analysis, modeling, mathematics or other quantitative subject area.
* OR advanced degree/designation in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, or other quantitative subject area and 6 years work experience in a quantitative subject area relevant to risk management
* OR PhD in Economics, Finance, Statistics, Mathematics, or other quantitative subject area and up to 4 years work experience in a quantitative subject area relevant to risk management.
What sets you apart:
* 5+ year 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 or Mantas, preferrable modern systems leveraging Machine Learning Algorithm for Detection.
* A Ph.D. in a quantitative field. Advanced knowledge of statistical and machine learning models and techniques.
* ACAMS Certified
The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.
What we offer:
Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. The salary range for this position is: $138,230 - $264,200.
Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.
Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include 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, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals.
For more details on our outstanding benefits, please visit our benefits page on USAAjobs.com.
Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.
USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
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