VP, Data Science

General Summary

This position will lead Elevate’s Data Science efforts to develop, deploy, and maintain predictive models and decision processes for use in current account management strategies. The Vice President works cross functionally with IT, Risk, Operations, and Portfolio teams to develop a platform to drive business strategy for loss forecasting, credit line increases and decreases, cross sell, collections, and other critical functions of account management. The Vice President leads teams of data scientists to support data and model development, as well as model and strategy implementation across all U.S. products.

Principal Duties and Responsibilities

• Lead and manage a team of data scientists who develop data and algorithms to support account management strategies
• Utilize internal and external data sources to support a Hadoop-based account management data and decision platform
• Develop data and algorithms to support fraud mitigation, credit loss reduction, and other key metrics for current accounts in each of Elevate’s U.S. portfolios
• Collaborate with Operations and Risk Management leaders to develop data, model, and strategy requirements to support improved collections performance
• Partner with IT resources to ensure effective curation and governance of account management data resources
• Develop and maintain strong relationships with IT, Risk Management, and other support functions to ensure alignment of Data Science initiatives with Company objectives.

Experience and Education

• Advanced degree (MA/MS/MBA/PhD/DSc) in an analytical field preferred
• 10+ years of experience developing and deploying statistical models and scoring algorithms
• Demonstrable experience with strategy development in a lending environment using advanced statistical models
• Demonstrable experience in data development and management in advanced databases
• Management experience, preferably of large groups of quantitative analysts and modelers

Required Skills, Abilities, Soft Skill Factors

• Ability to thrive in a dynamic and fast-paced environment and drive change, and collaborate effectively with a variety of individuals and teams
• Knowledge of credit and credit bureau data
• Demonstrable expertise with statistical modeling techniques and algorithms
• Demonstrable expertise with multivariate statistical methods, including cluster analysis, linear PCA, and factor analysis
• SAS and/or R experience
• Understanding of databases and database architecture
• Strong analytical, statistical, and problem-solving skills
• Strong planning, organizational, people, and project management skills
• Excellent interpersonal, verbal and written communication skills

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