Hybrid Lead Data Scientist - Credit Risk & Model Validation

Socket.dev; Chicago (IL); Hybrid; USD 106,000 - 140,000; Full time

Benefits offered by this job

Health, dental, vision insurance

401(k) matching

PTO & holidays

Sabbatical program

Summer hours

Parental leave

DEI groups

Recognition program

Volunteer day

Job summary

Enova International is seeking a Lead Data Scientist to advance credit risk modeling and validation. You will develop, test, and validate models used to determine lending criteria, mentor teammates, and collaborate with cross-functional partners to drive risk and operational strategies.

You will combine statistical expertise with Python programming and SQL experience to interpret data, build robust validation reports, and support production deployments across our analytics platform.

Qualifications

• Experience developing or independently validating advanced credit risk models.
• 5+ years in quantitative analysis in financial services; leading complex validation projects preferred.
• Strong knowledge of statistical models and risk-management methodologies.
• Proficient in Python with ability to write custom data-analysis programs.
• Experience with relational databases, e.g., SQL.
• Ability to explain complex quantitative concepts to technical and non-technical stakeholders.

Responsibilities

• Lead and perform model validation of credit risk models.
• Prepare model validation reports and technical documentation.
• Provide technical guidance and mentorship in validating models for production.
• Interact with stakeholders to gather information and provide effective challenge.
• Support model releases to production.
• Monitor model performance dashboards and raise concerns.
• Improve validation methodologies and governance using data and automation.

Skills

Credit risk models

Quantitative analysis

Model validation

Statistical methods

Stakeholder communication

Tools

Python

SQL

Job description

Enova International is seeking a Lead Data Scientist to advance credit risk modeling and validation. You will develop, test, and validate models used to determine lending criteria, mentor teammates, and collaborate with cross-functional partners to drive risk and operational strategies.

You will combine statistical expertise with Python programming and SQL experience to interpret data, build robust validation reports, and support production deployments across our analytics platform.