Lead Data Scientist - Fraud (Hybrid)

*We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas or take over sponsorship at this time.*

About the role

Staying a step ahead of fraudsters takes an inquisitive mind, an appetite to dig deeper, and the imagination to shed new light on how we fight fraud — and here, it all starts with data. As a Lead Data Scientist on Enova's Fraud Analytics team, you'll be the quantitative engine of our fraud prevention effort. You'll develop, enhance, and test the models and pattern-recognition pipelines that surface emerging fraud trends across our lending products — then work hand-in-hand with our Fraud Operations team, who investigate the individual applications your models flag. Their findings (the false positives and false negatives) come back to you to sharpen the identifying characteristics and pivot the approach. It's a fast, iterative loop, and you sit at the center of it.

The broader Enova Analytics department consists of 100 quantitative professionals dedicated to using the latest cutting-edge techniques to drive business value: providing customers with access to fast, trustworthy credit while managing risk. Our company-wide, data-driven culture means you spend less time presenting and more time on the fun part: crunching data.

Key responsibilities

• Develop, deploy, and monitor models and pattern-recognition algorithms to detect emerging and shifting fraud trends across one or more lending products
• Write customized programs in Python for meaningful data analysis and predictive modeling, and query large, complex datasets in SQL
• Partner closely with Fraud Operations through the full detection loop — pulling data together, surfacing suspicious patterns, and incorporating their investigation results to refine features and reduce false positives/negatives
• Conduct ad hoc analysis on large, complex datasets to scope new or changing fraud trends and re