Pricing & Credit Model Analyst; Hybrid Position

It Starts Here

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. It’s a chance for driven professionals to grow, learn, and make a real difference.

The Sr. Specialist, Pricing & Credit Model Analyst is responsible for developing pricing and risk‑based models to optimize Auto loan pricing strategies. This role also involves development and maintenance of sophisticated empirical models – including credit scoring models. The position is highly quantitative in nature and requires an individual capable of taking a "hands‑on" approach to data analysis. You will work closely with credit risk, finance, data science, and product teams to deliver actionable insights that balance risk, profitability, and competitiveness.

This position blends strategic business problem solving with quantitative modeling expertise. You will work closely with leadership to translate complex data insights into clear business actions.

• Develop a thorough understanding of the firm’s operations and business practices.
• Apply statistical techniques to analyze trends and uncover risks and opportunities relative to portfolio management and originations.
• Utilize data mining and statistical techniques to develop analytic insights, sound hypotheses, and informed recommendations.
• Develop pricing frameworks that balance yield, risk, and volume objectives. Incorporate credit risk, customer behavior, collateral trend and market data into pricing algorithms.
• Develop actionable recommendations to improve underwriting strategy, portfolio performance, and credit policies.
• Explore opportunities to enhance Dealer Management program to grow our business with top‑performing partners.
• Participate in the construction of complex mathematical models – including credit origination and customer behavior scorecards – which directly support critical decision‑making processes.
• Contribute to continuous process improvements in data quality, reporting, and automation.
• Liaise with IT and other internal teams to define requirements and ensure the timely and accurate delivery of data elements for analytic projects, changes to Pricing & Policy.
• Encapsulate analytic findings into executive‑level summary documents to support senior management decision‑making.

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Bachelor’s Degree or equivalent work experience:
  Statistics, Economics, Operations Research, Applied Mathematics, or a related quantitative discipline required or equivalent experience.
• Master’s Degree in Statistics, Economics, Operations Research, Applied Mathematics, or a related quantitative discipline required or equivalent experience. (Preferred)
• Ph.D. in Statistics, Economics, Operations Research, Applied Mathematics, or a related quantitative discipline required or equivalent experience. (Preferred)
• 3+ Years Analytics in Financial Services Industry or equivalent. (Required)
• 3+ Years Indirect subprime Auto Financial Services Industry experience. (Preferred)
• 3+ Years Prior experience developing credit scoring models. (Preferred)
• Familiarity 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. (Preferred)
• Demonstrated ability to use SQL and SAS to extract data from multiple data sources. Working knowledge of Python/R. (Preferred)
• Demonstrated ability to merge, concatenate, and prepare extremely large datasets for statistical analysis and…