Risk Management Statistical Modeler - Libertyville, IL Back>>

Risk Management Statistical Modeler


Identify opportunities to apply statistical analyses to improve business performance. Develop and implement statistical models that enable the company to efficiently and effectively monitor the
performance of the US and Canadian lease, balloon and commercial portfolios.

-Assist in the design, development and maintenance of predictive models for consumer credit portfolio used for forecasting probability of defaults (PD), loss given default (LGD) and exposure at default (EAD) based upon customer payment and delinquency behavior, credit profile and other portfolio and market dynamics
-Partner with Accounting and colleagues within Risk Management in establishing adequate credit loss provisions for US and Canadian consumer portfolios; conduct sensitivity tests on the models to accommodate qualitative overlays related to the economy, used car market volatility, changes in credit policies and collection strategies and other factors that may affect future portfolio performance; work with internal and external audit partners to gain acceptance on the loss reserving methodology and provide technical support in order to meet audit and regulatory requirements
-Assist in the validation of US and Canadian internal credit acquisitions scorecards though the use of KS-statistic (or similar metrics such as ROC curve, Gini coefficient and Divergence), population stability index (PSI), characteristic analysis and bad rate analysis; perform similar task on back-end/behavior scorecards as needed
-Support the on-going Data Warehouse restructuring project through testing (i.e. validating mapping logic and table relationships); work with IT and Data Governance Committee to identify and resolve data quality issues; maintain and develop various databases, technical models and reports required to support research, data gathering and analytical responsibilities
-Assist in the maintenance of the commercial portfolio’s dealer rating system including validation of model performance (i.e. PD forecasts and ability to rank-order accounts), update of seasonal indices and recalibration of forecasts; support the Commercial Credit Risk team on future model updates and redevelopment
-Take lead in the development and implementation of a forecasting model to quantify value-at-risk relating to interest rate exposure using Farin’s Foresight software or similar packages; establish a partnership with Treasury and Accounting & Controlling group to collect required financial data and review validity of model assumptions
-Help improve existing residual value setting model; perform elasticity, sensitivity and scenario analysis using Black Book, ALG, Auctionet and other third-party and internal data to identify residual value strategies that will optimize results; provide analytical support relating to lease pull-ahead, extensions and similar marketing initiatives to help business leaders make informed decisions
-Collaborate with other team members to determine if quantitative analysis and modeling is required to improve business performance
-Educate colleagues on proper statistical principles and methodology; sell ideas and conclusions in a clear, concise manner to colleagues with limited statistical background
-Identify areas of opportunity where statistics can improve business results or increase process efficiency; demonstrate effective planning, research and implementation of statistical models
-Provide inputs to the Statistical Modeling group to ensure projects and initiatives are aligned with Risk Management’s strategy map

-5+ years related professional experience is required for this position
-3 Years Experience in a statistical field
-3 Years Working in a business environment
-2 Years Data Analysis or Modeling with large transactional database.
-Bachelor Degree in Statistics, Applied Mathematics, Econometrics, Operations Research or similar quantitative field of study is required
-Analytical and conceptual thinking - using logic and reason, creative and strategic
-Computer Savvy - highly skilled in software use and programming
-Communication - excellent skills in written and visual communication
-Advanced knowledge of concepts, principles, standards, practices and techniques relating to statistical modeling, analysis, interpretation and communication
-Advanced knowledge of advanced applied statistical methodologies including least squares regression, logistic regression and credit scoring, sampling methodologies, time series analysis, generalized linear modeling, cluster analysis, categorical data analysis, decision trees and other multivariate methodologies
-Ability to conduct large scale projects and research through all stages: concept formulation, definition of metrics, determination of appropriate methodology, research evaluation and final research report
-Demonstrated understanding and experience with relational datasets, data warehouses, data mining and data analysis techniques
-Excellent computer skills and techniques using multi-variant statistical analysis packages (SAS, SPSS, Knowledge Studio) and other reporting and data analysis tools (Business Objects, Access, Excel)
-Established data mining skills using existing databases, third party-provided data, or creating your own when necessary
-Ability to “think out of the box” and use unconventional methods where necessary
-Specialized ability to communicate highly technical subjects to the senior executives and others who have limited background in mathematics or statistics

Jobs, Chicago area, Risk Management Statistical Modeler, Statistics, Data Analysis, Data modeling, Mathematics


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