Lead Data Scientist - Fraud (Hybrid)
About The Position
As a Lead Data Scientist on Enova's Fraud Analytics team, you will be the quantitative engine of our fraud prevention effort. You will develop, enhance, and test the models and pattern-recognition pipelines that surface emerging fraud trends across our lending products. You will work closely with the 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. The broader Enova Analytics department consists of 100 quantitative professionals dedicated to using the latest cutting-edge techniques to drive business value. Our company-wide, data-driven culture means you spend less time presenting and more time on the fun part: crunching data.
Requirements
- 5+ years of experience in analytics, applied machine learning, or quantitative modeling
- Hands-on fraud experience required — fraud analytics, fraud strategy, or risk modeling, ideally in fintech or lending
- Advanced Python and SQL; experience owning models end-to-end — design through deployment and monitoring — on large-scale transactional data
- Track record of translating analysis into business strategy and communicating with senior stakeholders
- Previous leadership experience mentoring teammates, driving team initiatives, and shaping priorities.
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 recommend risk, verification, and operational strategies
- Communicate findings clearly to cross-functional partners, provide requirements, 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 help coordinate their work with business priorities.
Benefits
- Health, dental, and vision insurance including mental health benefits
- 401(k) matching plus a roth option
- PTO & paid holidays off
- Sabbatical program
- Summer hours
- Paid parental leave
- DEI groups
- Employee recognition and rewards program
- Charitable matching and a paid volunteer day
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
