Associate, Model Development (Hybrid Position)

Santander is a global leader and innovator in the financial services industry and is evolving from a high-impact brand into a technology-driven organization. Our people are at the heart of this journey and together, we are driving a customer-centric transformation that values bold thinking, innovation, and the courage to challenge what's possible. This is more than a strategic shift. 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. The position is highly quantitative in nature and requires an individual capable of taking a "hands on" approach to data analysis. 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 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. 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. 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.Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. 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. - 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. 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. ~ Ability to effectively explain advanced mathematical concepts, techniques, and analyses to a business audience. ~ Ability to translate analysis into a clear business plan. ~ Ability to delegate and co-ordinate multiple tasks related to the development and monitoring of statistical models. ~ Established work history or equivalent demonstrated through a combination of work experience, training, military service, or education. Applicants must be legally authorized to work in the United States on a full-time basis without requiring employer sponsorship to commence employment. For hourly positions (non-exempt), the annual range is based on a 40-hour work week. The exact compensation may vary based on skills, experience, training, licensure and certifications and location. Risk Culture: We embrace a strong risk culture and all of our professionals at all levels are expected to take a proactive and responsible approach toward risk management. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, genetics, disability, age, veteran status or any other characteristic protected by law. Depending on location, occasional moving and lifting light equipment and/or furniture may be required. You may be evaluated in part based upon your performance of the tasks listed in this job description. This job description is not a contract for employment and either you or the employer may terminate your employment at any time for any reason. We are committed to providing an inclusive and accessible application process for all candidates. 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