The Statistical Analyst is responsible for the collection, management, and analysis of internal data to support modeling and collections strategies across all revenue channels. The Statistical Analyst is also responsible for the score-based valuation of existing collections portfolios at all levels of aggregation and/or the development of credit scores to support valuation and collections activities; collaborates with group analysts as they specify and validate collections strategies, maintain collections forecasts, and revise and improve our predictive models. This position works with partners in Marketing, Acquisitions, and Operations to aid in the development and implementation of score-based and logic-based collections practices. This role is equally comfortable discussing the academic merits of a statistical approach or the ways in which a forecasting model will impact a business channel's revenue and cost expectations.

Responsibilities:

  • Facilitate the use of Decision Science methodologies throughout the servicing operation.

  • Implement, track, and validate score-based collections strategies.

  • Responsible for the collection, management and analysis of internal data to support modeling and collections strategies.

  • Work closely with Managers during the creation and validation of valuation products.

  • Work with partners in Operations to aid in the development and implementation of score-based and logic-based collections practices.

Work Experience:

Required: 0-3 years of relevant experience in an academic, financial services, technical or medical field. Proficiency with base SAS and SAS / STAT; expertise with formal statistical methodologies; strong knowledge of some or all of the following: logit models, generalized linear models, categorical data analyses, ANOVA and regression. Proficiency with MS Office, particularly Excel.

Preferred: Expertise in modeling risk-based outcomes; familiarity with the logic of credit scoring and the development of marginal economic analysis; experience with traditional longitudinal and cohort analyses. Advanced proficiency with MS Office, particularly Excel.

Education:

Required: Bachelor; Statistics, Engineering or a quantitative science

Preferred: Master/Advanced; Statistics, Engineering or a quantitative science


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