Director, Modeling Analytics-AML/Sanctions (Remote Available)
Company: USAA
Location: Lutz
Posted on: January 13, 2022
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Job Description:
Purpose of Job We are seeking a talented Director, Modeling
Analytics, for either our San Antonio, TX, Phoenix, AZ,
Charlotte-Concord, NC or Tampa, FL facility. This person may also
work remotely in a 100% Remote Work Environment.
Responsible for reviewing monitoring scenarios and controls, system
controls, operational reports, as well as model design and
development with a goal of adding rigor to the overall monitoring
program. Key considerations will include review of control
development, testing, and use, control classification, and control
documentation.
Effectively manages and leads a team that develops and analyzes
data to predict business results or member behavior. Technically
proficient in statistics, mathematics, and tools used in predictive
modeling. Partners cross-functionally with business to deliver
breakthrough analytical solutions to support a winning strategy in
a continually changing business environment.
Job Requirements
About USAA
USAA knows what it means to serve. We facilitate the financial
security of millions of U.S. military members and their families.
This singular mission requires a dedication to innovative thinking
at every level.
Primary Responsibilities:
Identify and manage existing and emerging risks that stem from
business activities and the job role.
E nsure risks associated with business activities are effectively
identified, measured, monitored, and controlled.
Follow written risk and compliance policies and procedures for
business activities.
Builds and manages a strong modeling analytics team.
Establishes performance objectives and provides ongoing feedback
and coaching.
Frequently interacts with business partners to identify
opportunities for predictive analytics to drive business strategy
and results forward.
Delivers insight to senior leadership on a regular basis.
Lead the development, enhancement and implementation of statistical
and other quantitative models to support loss prediction, assess
member value, predict member behavior or financial performance and
other business applications.
Full ownership of the model development process and relationship
with the business customer: from conceptualization through data
exploration, model selection and validation,
implementation, business user training and support.
Develops and provides subject matter expertise on the current and
emerging predictive modeling techniques for various areas within
the financial services industry.
Monitors and understands emerging technology that can affect
modeling and potential business risk.
Educates and coaches peers and business partners to leverage
predictive analytical solutions.
Coordinates with legal counsel to ensure regulatory compliance
regarding model design and the acquisition and usage of data for
segmentation and modeling purposes. .
When you apply for this position, you will be required to answer
some initial questions. This will take approximately 5 minutes.
Once you begin the questions you will not be able to finish them at
a later time and you will not be able to change your responses.
Minimum Requirements:
Bachelor's degree in Statistics, Economics, Engineering,
Mathematics, Actuarial Sciences or related field or 4 additional
years of related experience beyond the minimum required may be
substituted in lieu of a degree.
8 years of experience in statistical analysis and model
development; or if Advanced degree in Statistics, Economics,
Engineering, Mathematics, Actuarial Sciences or related field then
6 years progressive data modeling experience.
3 years of team lead or management experience required.
Expert knowledge of key econometric and statistical techniques
(predictive modeling, logistic regression, survival analysis,
design of experiments, decision trees, data mining methods, and
other advanced statistical and econometric techniques).
Knowledgeable in Data Modeling and Data warehouse concepts
Experience in data modeling (dimensional and other techniques using
modeling tools) along with transactional systems, data warehouses
and data marts.
Proficiency with design, conceptual, logical and physical data
models
Preferred Experience:
Experience leading a quantitative team and/or significant modeling
projects
Experience in fraud or compliance risk modeling development
Strong SAS, SQL, R, and/or Python programming
Experience with visualization business intelligence tools (BI)
Experience working with business and risk control
Clear and concise communicator
Ability to communicate complex concepts
CAMS Certification
Attachments
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.
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
position. The salary range for this position is: $117,600 -
$211,700* (this does not include geographic differential it may be
applied based on your work location)
Employees may be eligible for pay incentives based on overall
corporate and individual performance or 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.
Please click on the link below for more details.
USAA Total Rewards
Relocation assistance is not available for this position.
Keywords: USAA, Brandon , Director, Modeling Analytics-AML/Sanctions (Remote Available), Executive , Lutz, Florida
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