VP, Risk Policy Lead
Wilmington, DE, USA | Citi Private Bank
Job Description:71 people have viewed this job
Optimizing existing collections strategies and developing/testing new strategies and efficiencies for 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.
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 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.
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.
Minimum 5+ years of 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.
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.
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