Consumer Credit Risk - Statistical Modeler - Hammond, IN

Company Name:
FF&C Mgt
Shall apply statistical techniques for customers in the retail banking and consumer credit domain ranging from propensity models for customer acquisition and retention, portfolio models, cross-sell applications and more in this client facing role.
Shall perform:
Survival analysis, Bayesian analysis, discriminant, correspondence, multi-dimensional scaling, decision trees, GAM, text mining and geospatial analysis.
GLM multiple regression, log-linear regression, logistic regression, and variable selection.
Multivariate analysis - Clustering, factor, principal component, etc.
Time Series forecasting.
Working with Excel, SAS, SQL, R or similar software.
Candidate must possess a Masters or above in statistics, Math,or similar field and at least 2 years modeling experience with a history of working with banking, insurance, mortgage, or credit lending services.
State of the art technology with salary to $140,000 and competitive benefits including; medical, dental, and vision; short-term and long-term disability; flexible spending accounts; matched 401(k); life insurance; retirement plan and more.
For complete details contact Greg Foss at:
(609) 584-9000 ext 270
Or submit resume online at:
Or email to:
Please reference #35771 when responding.
Education Requirements: Bachelor Degree
Minimum Experience Requirements: 2-5 years
Job City Location: Hammond
Job State Location: IN
Job Country Location: USA
Salary Range: $80,000 to $140,000
WE ARE AN EQUAL OPPORTUNITY EMPLOYER and our employment decisions are made without regard to race, color, religion, age, sex, national origin, handicap, disability or marital status. We reasonably accommodate individuals with handicaps, disabilities and bona fide religious beliefs. Jobs Career Position Hiring. CONSIDERED EXPERIENCE INCLUDES: http://najobbank.com www.najobbank.com Top 10 Job Site Top 10 Careers Site Predictive Modeler Modeling Statistician Credit Risk Management Analytics Consumer Analyst Loan Lending SAS
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