Senior Specialist, Model Development

Santander

Sr. Specialist developing and maintaining empirical models at Santander, focusing on credit scoring and risk analysis.

Posted 7/6/2026full-timeRemote • Texas • 🇺🇸 United StatesSenior💰 $65,625 - $145,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in developing and maintaining empirical models, particularly in credit scoring, utilizing statistical techniques and data analysis to inform business decisions. Proficient in SQL and Python for data extraction and manipulation, with a strong understanding of financial services and regulatory compliance.

Highest-signal resume keywords

Credit Scoring Model DevelopmentStatistical Analysis TechniquesSQL Data ExtractionPython ProgrammingFinancial Services Analytics

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingLogistic RegressionHypothesis TestingNeural NetworksDecision TreesData MiningMathematical ModelingData PreparationComplex Pivot TablesVariable Reduction Techniques

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationConfidentiality MaintenanceBusiness Plan Translation

Tools & Technologies

SASSQLPythonMS Excel

Industry Keywords

Nonprime Auto LendingCredit Bureau DataFinancial Services IndustryModel ValidationU.S. Federal Reserve Regulations

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Responsible for developing and maintaining sophisticated empirical models - including credit scoring models - for a nonprime auto lender
Summary and reporting of information to a variety of internal and external clients
Interact with many other departments to achieve overall company objectives
Participate in the construction of complex mathematical models – including credit origination, pricing and customer behavior scorecards
Develop underlying assumptions, theory, empirical evidence, and conceptual soundness of statistical and mathematical models
Apply statistical techniques to analyze trends and uncover risks and opportunities
Use internal and external data sources to create robust model development datasets
Ensure modeling projects are conducted in accordance with established company policies and mathematical modeling practices
Identify modeling needs and communicate them to the Director Quantitative Modeling
Assess department procedures for accuracy and completeness
Utilize data mining and statistical techniques to develop analytic insights, sound hypotheses, and informed recommendations
Encapsulate analytic findings into executive-level summary documents for senior management decision-making
Liaison with IT and other internal teams to define requirements and ensure timely and accurate delivery of data elements
Provide requisite information in support of independent model validation activities
Develop understanding of the firm’s operations and business practices
Support Model Validation and documentation of models in accordance with internal policies and U.S. Federal Reserve regulations

Requirements

What you’ll need

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: Statistics, Economics, Operations Research, Applied Mathematics, or a related quantitative discipline required or equivalent experience. - Preferred
Ph.D.: Statistics, Economics, Operations Research, Applied Mathematics, or a related quantitative discipline required or equivalent experience - Preferred
3+ Years Analytics in Financial Services Industry. - Required
3+ Years Indirect subprime Auto Financial Services Industry experience. - Preferred
3+ Years Prior experience developing credit scoring models preferred. - 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 strongly preferred
Prior experience using Python, or SAS, SQL
Demonstrated ability to use SQL and Python to extract data from multiple data sources
Demonstrated ability to merge, concatenate, 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
Strong written and verbal communication skills
Ability to maintain confidentiality

Benefits

Comp & perks

Competitive salary
Fair and competitive rewards package
Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development opportunities