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Tech Stack
Tools & technologiesPythonSQL
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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Statistical ModelingLogistic RegressionHypothesis TestingNeural NetworksDecision TreesData MiningMathematical ModelingData PreparationComplex Pivot TablesVariable Reduction Techniques
Soft Skills
Strong Written CommunicationStrong Verbal CommunicationConfidentiality MaintenanceBusiness Plan Translation