Data Scientist - Fraud Risk at Rain
New York, NY
$50,000–$999,999
Jul 30, 2026
New York, NY
Nov 9, 2026
What this job asks for AI summary
A fraud risk analytics role at a stablecoin payments infrastructure company, focused on building and owning real-time monitoring systems, ML-powered risk controls, and fraud dashboards. The position sits at the intersection of data science and fraud strategy — designing A/B experiments, implementing predictive models, and communicating results to leadership and external partners. Best suited to someone with hands-on fraud risk experience in a fast-moving fintech environment.
Mid level · 3+ years · Remote · Bachelor's required · Full-time
Quick apply — this platform usually takes a CV and a few fields.
Posted 4 times — it's one opening, so apply once.
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 47,000 people nationally plausibly meet what this posting asks for (data scientists). range 13,800–70,500
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 $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 1, 2026. It is a model, not a headcount.
Why we read it this way (6)
No work location is specified beyond flexible/remote-friendly language and US-centric benefits; the role appears to be remote-eligible in the US but no city or metro is stated.
The 3+ years requirement is scoped specifically to fraud risk strategy and experimentation, not general engineering experience — classified as total experience minimum given the role-level framing.
The degree requirement lists several quantitative fields (Statistics, Mathematics, Engineering, Computer Science) as acceptable; a bachelor's in any of these is a hard gate.
SOC classification is Medium confidence: the role blends data science (ML modeling) with fraud analytics/BI (dashboards, metrics, reporting). 15-2051 was chosen because ML model design and implementation is the primary technical differentiator called out in requirements; 15-2031 is a plausible alternative given the heavy analytics and reporting emphasis.
'AI-assisted data analysis / data science tooling' appears only under the Nice to have section.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): AI-assisted data analysis.
Read the full posting
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