Senior Fraud Data Scientist — AI-Driven Risk Lead

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

Benefits offered by this job

Hybrid work Tue-Thu in-office

Health, dental, and vision insurance

401(k) matching with Roth option

Paid time off

Sabbatical program

Summer hours

Parental leave

DEI groups

Volunteer day

Job summary

Enova International is seeking a Lead Data Scientist for the Fraud Analytics team to drive fraud prevention through advanced models and pattern-recognition pipelines on lending products.

You will develop, deploy, and monitor models in Python and SQL, collaborate with Fraud Operations, and translate findings into actionable risk strategies while mentoring team members in a fast-paced fintech environment.

Qualifications

• 5+ years of analytics, applied ML, or quantitative modeling.
• Hands-on fraud experience in fintech or lending preferred.
• Strong communication with senior stakeholders.
• Leadership experience mentoring teammates and shaping priorities.

Responsibilities

• Develop, deploy, and monitor models and pattern-recognition algorithms to detect fraud trends across lending products.
• Write Python programs for data analysis and predictive modeling; query large datasets in SQL.
• Collaborate with Fraud Operations throughout the detection loop; refine features based on investigation results.
• Conduct ad hoc analysis on large datasets to scope new fraud trends and recommend risk strategies.
• Communicate findings clearly to cross-functional partners and support implementation.
• Help improve underwriting and verification processes from a fraud-risk perspective.
• Apply AI in production applications to streamline fraud prevention processes.
• Manage team members and coordinate their work with business priorities.

Skills

Fraud analytics

Leadership

Communication

Stakeholder management

Mentoring

Tools

Python

SQL

Model deployment

Job description

Enova International is seeking a Lead Data Scientist for the Fraud Analytics team to drive fraud prevention through advanced models and pattern-recognition pipelines on lending products.

You will develop, deploy, and monitor models in Python and SQL, collaborate with Fraud Operations, and translate findings into actionable risk strategies while mentoring team members in a fast-paced fintech environment.