| Job Description: | The Role:
The Senior Risk Modeling Analyst develops statistical models and strategies to manage risk, reduce
fraud, or increase revenue through advanced techniques.
This key role also develops models to improve the new customer acquisition, authorization and portfolio
management strategies. Monitors and evaluates scoring models and other advanced predictive
technologies and monitors the performance of existing models.
What You’ll Do:
• Develop, implement and maintain modeling and analytics projects performed within
Credit Policy group, including models for fraud, credit, revenue, response, etc.
• Design, test, and implement customer-level propensity models
• Develop offer segmentation, testing, and recommendations
• Develop and implement clustering models to classify high revenue customers and create
treatments strategies to encourage usage.
• Review opportunities to enhance model effectiveness by using new techniques, data, or
other methods
• Validate performance and track model effectiveness over time
• Effectively communicate with team and corporation throughout the process, including
model results
• Coordinate with IT to provide specification for model implementation in the authorization
process.
• Work with internal and external partners to develop, test, and implement new models,
such as an Incremental Response, Incremental Value, Clustering, and other models
• Develop and implement ad-hoc analysis to support the needs of the organization
• Serve as a statistical expert in order to support the modeling and analytical needs of the
organization
• Utilize skills to constantly automate analytics and modeling to streamline the process and
time for delivery
• Make recommendations based on sound statistical insights which positively impact the
business
What You’ll Need to Bring:
• Strong proficiency in SQL and data preparation for statistical analysis
• Strong SAS skills, including SAS/BASE, SAS/STAT, SAS/GRAPH, and SAS/Macros
• Extraordinary quantitative, modeling and analytical skills
• Effective organizational and time management skills
• Strong interpersonal skills with the ability to work with all levels of management
• Demonstrated problem solving skills utilizing data and analytic techniques including but not
limited to segmentation, conjoint, discriminant, and regression analyses; market mix modeling,
discrete choice modeling, etc.
• Expertise in applying statistical techniques to drive business decision-making
• Ability to manage multiple priorities, projects, and deadlines simultaneously
• Experience developing, validating and deploying account acquisition or authorization strategies
for consumer lending or payments products.
• Graduate level of education in quantitative field such as econometrics, statistics, management
science, applied mathematics or related field
• PhD in math, statistics or other appropriate field is highly desirable
• Minimum of 5 years of analytical, modeling, or marketing analytics experience |
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