Senior Data Scientist - Fraud (Hybrid) at Enova International
Chicago, IL
$96,000–$125,000from the description
Jul 27, 2026
Chicago, IL
Jul 29, 2026
What this job asks for AI summary
A Senior Data Scientist role on Enova's Fraud Analytics team, focused on building, deploying, and continuously refining fraud-detection models and pattern-recognition pipelines across lending products. The position sits at the center of a tight feedback loop with Fraud Operations, using their investigation results to sharpen model features and reduce false positives. It suits an experienced quantitative practitioner with hands-on fraud or risk modeling background who is beginning to grow into people leadership.
Senior level · 4+ years · Chicago, IL · Full-time
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 1,300 people in the Chicago, IL area plausibly meet what this posting asks for (data scientists). range 690–1,700
Applicant volume Heavy — This req sits in a large pool with little in its requirements to thin it, and auto-apply tools fire at everything in the occupation. Applying early and leading with the rare skills below is what gets read.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $110,007 (middle half $86,460–$141,249). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (5)
Location is not explicitly stated in the posting; Enova is headquartered in Chicago, IL, so the CBSA has been inferred from the company's known location. The posting does not confirm remote eligibility, so remote is marked false.
The alt SOC (15-2031 Operations Research Analysts) is noted because the role blends statistical/ML modeling with business strategy and fraud risk analysis — a genuine occupational overlap — but the ML/modeling emphasis tips it to Data Scientists.
Fraud analytics experience is listed as a hard requirement ('fraud experience required') but names no specific tool or platform; it is captured as a named domain skill rather than a generic concept because the posting explicitly gates on it.
'AI in production applications' appears in the responsibilities section (not requirements) and names no specific tool or framework, so it is captured as a preferred skill under the canonical name 'AI'.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): predictive modeling.
Read the full posting
The employer publishes the full description on their own site — read it there ↗. Or sign in to read it here — it's free, and it also lets you track this application.