Vacancy expired!
The Data Analytics Specialist Sr, Loss Forecasting position will be based in Herndon, VA or Ajax, ON, with a role classification of Hybrid.
Role Summary: The Data Analytics Specialist Sr, Loss Forecasting - NAR assists in identifying opportunities to apply statistical analyses to improve business performance. Supports the design, development, implementation and validation of predictive models that enable the company to efficiently and effectively manage the performance of retail and lease portfolios with $25B in combined net receivables. Supports the data governance functional activities related to metadata management, development and implementation of data quality processes and data policies. Supports model risk management efforts to monitor model performance and govern all assumptions utilized in models. Helps provide strategic guidance to steer management towards data-driven business decisions that impact credit policies, account management strategies, and credit loss provisioning. Role Responsibilities:- Work with the Statistical Modeling Team- Consumer Credit in all efforts related to the design, development, testing and execution of the IFRS9 impairment models for the consumer credit portfolio used for calculating expected credit loss (ECL) through probability of defaults (PD), loss given default (LGD) and exposure at default (EAD) based upon customer payment and delinquency behavior, credit profile, macro-economic trends and other portfolio and market dynamics (35%)
- Support all quarterly audit related activities including, but not limited to, providing external auditors with all supporting data and documentation to ensure smooth quarter closings (20%)
- Support Risk Management's efforts to collaborate with Accounting and Controlling in establishing adequate credit loss provisions for VCI's & VCCI's consumer and commercial credit portfolios. Conduct sensitivity tests on the models to accommodate qualitative/quantitative overlays related to the economy, used car market volatility, changes in credit policies, collection strategies and other factors that may affect future portfolio performance. Explain to Controlling executive Stakeholders variances in monthly provisions, vs. Budget and vs. Planning Round. (20%)
- As needed, assist the Consumer Credit Risk Portfolio Management team in analyzing credit risk data and emerging trends to develop, test and optimize risk factors related to credit and collection policies; also assist in validating and testing the effectiveness and the impact of credit policies and new products/programs on portfolio delinquencies and losses; this includes development of new reports or modification of existing reports in SAS (15%)
- Represent the Risk Management consumer credit team in the Data Stewards and Resource Sub-committee. Work with the data stewards to develop data quality validation processes and partner with cross-functional users of the data warehouse to identify operational and reporting data quality issues. As needed, work with IT and the business in identifying solutions and testing data fixes (5%)
- Support ad hoc requests in areas related to related to consumer portfolio risk (5%)
- Required 5+ years of professional experience
- 2+ years working in a Predictive Analytics or Statistical Modeling-related role
- Master's Degree in a quantitative discipline: Statistics, Mathematics, Economics, Finance, Operations Research, Data Science; or, Bachelor's degree in quantitative discipline + MBA
- 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
- Ability to effectively communicate technical subjects to business stakeholders and audience who have limited background in mathematics or statistics
- Analytical and conceptual thinking - ability to understand business problems and develop data-driven solutions
- king knowledge of basic statistical analyses including regression analysis, time series forecasting and other multi-variate analyses
- Ability to work effectively across portfolio risk teams and functional areas teams
- Strong communication and presentation skills targeting a variety of audiences
- Demonstrable strong working knowledge of SAS Enterprise Guide, ability to write/ edit macros and automate processes
- Experience writing SQL queries and utilizing BI tools like Tableau for visualizations and reporting
- Familiarity with other reporting and analytics tools: R, Stata, Python, RapidMiner, SageMaker
- Proficiency with Microsoft Office applications
- Minimal travel - 5%
- Flexibility to work remotely on as-needed basis
- Role may require occasional/seasonal work outside of normal working hours.
Vacancy expired!