Associate, Model Development (Hybrid Position)

About the role

The Associate, Model Development is responsible for supervising the development and maintenance of sophisticated empirical models - including credit scoring models - for a nonprime auto lender. This position is highly quantitative in nature and requires an individual capable of taking a "hands on" approach to data analysis.

Responsibilities

• Supervises the development of complex mathematical models – including credit origination and customer behavior scorecards - which directly support critical decision making processes and the company’s overall understanding of our business, the markets with.
• Develops the underlying assumptions, theory, empirical evidence, and conceptual soundness of statistical and mathematical models.
• Applies statistical techniques to analyze trends and uncover risks and opportunities relative to portfolio management and originations.
• Uses internal and external data sources to create robust model development datasets.
• Ensures modeling projects are conducted in accordance with established company policies and generally-accepted mathematical modeling practices.
• Identifies modeling needs and communicates them to the Director Quantitative Modeling.
• Periodically assesses department procedures for accuracy and completeness.
• Utilizes data mining and statistical techniques to develop analytic insights, sound hypotheses, and informed recommendations.
• Encapsulates analytic findings into executive-level summary documents to support senior management decision-making.
• Liaisons with IT and other internal teams to define requirements and ensure the timely and accurate delivery of data elements required for analytic projects.
• Provides requisite information in support of independent model validation activities.
• Actively participates in the professional development of junior-level statisticians.
• Develops a thorough understanding of the firm’s operations and business practices.
• Support Model Validation and documentation of models in accordance with Santander Consumer USA internal policies and U.S. Federal Reserve regulations (SR 11-07).

Qualifications

• Bachelor’s Degree: in related field or equivalent demonstrated through a combination of work experience, training, military service, or education - Required
• Master's Degree: in related field or equivalent demonstrated through a combination of work experience, training, military service, or education - Preferred
• 5+ Years Analytics in Financial Services Industry.
• 5+ Years Indirect subprime Auto Financial Services Industry experience. - Preferred
• 5+ Years Prior experience developing credit scoring models preferred. - Preferred
• Demonstrated experience with logistic regression models, segmentation and variable reduction techniques, hypothesis testing, neural networks, design of experiments, ANOVA, decision trees, and linear regression.
• Prior experience working with credit bureau data.
• Prior experience using SAS, particularly SAS base, SAS/STAT, PROC SQL, and SAS Macro programming. Additional knowledge of R preferred.
• Demonstrated ability to use SQL and SAS to extract data from multiple data sources.
• Demonstrated ability to merge, concatenate, clean, and prepare extremely large datasets for statistical analysis and mathematical model development.
• Demonstrated ability to create complex pivot tables in MS Excel.
• Demonstrated ability to use advanced analytical tools and techniques.
• Strong written and verbal communication skills.
• Ability to delegate and co-ordinate multiple tasks related to the development and monitoring of statistical models.
• Ability to maintain confidentiality.