# Data Scientist

**Company:** [Rain](https://hotfix.jobs/companies/rain)
**Location:** New York, NY
**Role:** Data Science
**Salary:** $50k – $1000k/yr
**Experience:** 3+ years
**Skills:** SQL, Python, Machine Learning, A/B Testing, Dashboards, fraud risk strategies, predictive modeling, Data Analysis
**Posted:** 2026-07-31

> Data Scientist on the fraud risk team building real-time monitoring, predictive ML models, and risk controls for payments and stablecoins. Requires 3+ years in automated fraud strategies, advanced SQL/Python, and quantitative degree.

## Job Description

## What you’ll do
- Own the metrics, dashboards, and reports that inform business strategy and decision-making
- Design and implement real-time monitoring systems for fraud signals and alerting thresholds
- Design, simulate, and implement real-time risk controls using real-time and offline predictive ML models
- Balance risk controls with customer experience by focusing on loss savings, reduced user friction, and margin improvement
- Partner with go-to-market teams to demonstrate the technical and business value of risk controls to customers
- Effectively summarize complex analytical results to leadership and non-technical stakeholders
- Assist partners when they have fraud concerns with their traffic

## What we're looking for
- Advanced proficiency in SQL and Python
- 3+ years hands-on experience working on automated fraud risk strategies and experimentation (A/B tests), including implementation of real-time and offline predictive ML models
- Skilled in designing, building, and maintaining dashboards and fraud risk metrics
- The ability to manage ambiguous problems and find solutions
- High autonomy, including the ability to prioritize your workload effectively
- Relevant quantitative bachelor’s (or higher) degree (Statistics, Mathematics, Engineering, Computer Science, etc.)

## Nice to have, but not mandatory
- Experience at a high-growth fintech company or financial services company
- Exposure to customer-facing or GTM-facing analytics or fraud issue triaging
- Background in identity risk, AML, payments fraud, or compliance analytics
- Fluency in AI-assisted data analysis / data science tooling

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