Senior Data Scientist - Credit Risk & Model Validation

Enova International; Chicago (IL); Hybrid; USD 96,000 - 125,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

PTO & holidays

Sabbatical

Summer hours

Parental leave

DEI groups

Volunteer day

Job summary

Enova International is seeking a Senior Data Scientist in the Chicago area to advance, validate and deploy credit risk models that determine lending criteria and verification procedures. You will perform independent validations, interpret data, and communicate findings to cross-functional teams to influence risk decisions.

The role requires advanced Python programming, SQL proficiency, and experience with credit risk modeling.

Qualifications

• Advanced programming in Python and ability to write customized data analysis programs.
• Experience in developing advanced credit risk models.
• 5+ years of quantitative analysis in financial services preferred.
• Experience with SQL and relational databases.
• Knowledge of statistical models in risk management.

Responsibilities

• Perform model validation of credit risk models.
• Prepare model validation reports and technical documentation.
• Assist analysts in validating and preparing their models for production.
• Interact with stakeholders to gather information about credit models and risk acceptances.
• Support model releases to production and monitor performance dashboards.
• Develop and test programs for automated model training and data manipulation.
• Use programming skills to create tools for data analysis.

Skills

Python

Credit risk models

Statistical modeling

SQL

Data analysis

Job description

Enova International is seeking a Senior Data Scientist in the Chicago area to advance, validate and deploy credit risk models that determine lending criteria and verification procedures. You will perform independent validations, interpret data, and communicate findings to cross-functional teams to influence risk decisions.

The role requires advanced Python programming, SQL proficiency, and experience with credit risk modeling.