- Optimizing existing late stage collections and recovery strategies and developing/testing new strategies and efficiencies for collections and recovery.
- Developing models using regression techniques or other statistical methodologies to classify accounts based on risk and treatment efficiency.
- Segmenting accounts using CHAID/CART methodologies to design champion/challenger collection and recovery strategies.
- Performing hypothesis testing using Statistical Experimental Designs to determine impact from new treatments that allows for causal measurements.
- Developing programming solutions using SAS and other programming and data querying tools to drive answers to analytic challenges and information for management decisions, observations and tracking.
- Conducting analysis using parametric or nonparametric statistics to conclude significant difference between test and control.
- Representing Risk Management on inter-departmental Process Teams.
- Participating in creating system requirements for new collections and recovery strategies and represent Risk Management throughout the development life cycle of a new strategy or policy.
- Collecting and interpreting data for ad hoc projects.
- Making recommendations and communicating the results to senior management.
- Evaluating effectiveness of current collections and recovery policies and strategies.
- Researching and applying new statistical techniques that can improve predictive power of models.
- Making significant contributions in the development of analytical tools used in the assessment of Collections and Recovery risk and policy.
- Maintain close relationships with key stakeholders in the structuring and approval of Investment Lending products.
- Four year degree in Statistics, Economics, Engineering, Finance, Mathematics, or a related quantitative field. Graduate degree is highly desirable.
- Minimum 4+ years of Credit Cards related experience or 5+ years related analytic experience using quantitative analysis, preferably in a risk context.
- Experience in statistical analysis with working knowledge of at least one of the following statistical software packages: SAS (preferred), SPSS, Statistica, S+ or some equivalent or R/ R Studio
- Experience with SQL programming in a UNIX environment.
- Demonstrated ability to synthesize, prioritize and drive results with a high sense of urgency
- Ability to independently develop robust statistical segmentation models.
- Establish solid cross-functional partnerships and networks to contribute and execute cross-functional and business initiatives.
- Outstanding communication and presentation skills, excellent interpersonal skills, thought leadership and should be comfortable working with ambiguity.
- The successful candidate will have demonstrable analytic and project management skills.
Bachelors level degree in Business, Statistics, Mathematics, or Engineering. Master’s degree preferred