Title: VP, Risk Policy Manager
Location: NY-Long Island City
The position requires managing loss mitigation projects from conception to rollout. These projects will include:
. Identifying new strategies and efficiencies in collections.
. Developing models using regression techniques or other statistical methodologies to classify accounts based on risk and collection treatment efficiency.
. Segmenting accounts using CHAID/CART methodologies to design champion/challenger collection strategies.
. Performing hypothesis testing using Statistical Experimental Designs such as Factorial Trials and Principle Analysis to determine impact from new treatments.
. Conducting P&L 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 loss mitigation 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 loss mitigation 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 loss mitigation risk and policy.
. Qualifications include a 4 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.
. Minimum 5 years 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.
. Experience with SQL programming in a UNIX environment.
. 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.
