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# Data Scientist - Model Validation (Hybrid)

- **Company:** Enova International, Inc.
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $87,000.0 - $110,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Computer Programming, Relational Databases, Python (Programming Language), Machine Learning, SQL Databases, Data Processing, Model Validation
- **Published:** June 24, 2026
- **Apply:** https://www.dice.com/job-detail/408177ac-dc30-4105-b54e-426b32668766

## About the Role

* Experience in developing advanced credit risk models
 * 3+ years of experience in quantitative analysis in the financial services industry is preferred but not required
 * Knowledge of statistical models in risk management
 * Advanced programming skills in Python and the ability to write customized programs for meaningful data analysis
 * Experience working with relational databases, such as SQL

## Description

As a Data Scientist, you will be one of Enova's most valuable team members. You will develop, enhance and test the company's models for use in determining the appropriate lending criteria and verification procedures. You will perform independent model validations to evaluate model fit for purpose, conceptual soundness, mathematical theory and assumptions, data/assumptions, and output reasonableness. At times, you may be asked to conduct ad hoc analysis using statistical and financial tools to recommend for risk management, marketing and operational strategies. You will demonstrate the ability to interpret and organize data, and communicate it effectively to cross functional teams to solve business problems, provide requirements and support implementation., * Perform model validation of credit risk models

 * Prepare model validation reports and write technical documentation
 * Assist analysts in validating and preparing their models for production
 * Interact with model stakeholders and business partners to gather information about credit models and risk acceptances
 * Support model releases to ensure they are quickly and accurately put into production
 * Monitor model performance dashboards, build alerts, and escalate concerns as appropriate
 * Support and improve automated model training processes by using data manipulation, and machine learning skills
 * Use your programming skills to develop and test programs for custom tool development


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