# Financial Crimes & Risk Data Analyst

**Company:** [Rain](https://hotfix.jobs/companies/rain)
**Location:** Remote
**Role:** Data Analytics
**Experience:** 2+ years
**Skills:** SQL, Chainalysis, Trm Labs, Elliptic, Python, pandas, Polars, Retool, AML, Bsa
**Posted:** 2026-03-05

> Analyzes financial crimes data to optimize transaction monitoring rules, investigates risk patterns, and builds dashboards for compliance teams at a fintech payments company. Requires 2+ years in risk/fraud analytics, strong SQL, and blockchain tools experience.

## Job Description

## Responsibilities
- Assist in continuously improving transaction monitoring rules across card, ACH, wire, and digital asset activity to increase detection quality and reduce false positives
- Conduct deep-dive investigations into emerging risk patterns and convert findings into scalable, production-ready monitoring logic
- Analyze alert and case data to evaluate rule performance (e.g., false positive rates, alert-to-case conversion, escalation outcomes) and recommend data-driven optimizations
- Partner with Compliance Investigations to identify typologies and ensure monitoring logic reflects real-world risk signals and regulatory expectations
- Support the design and refinement of onboarding and KYC/KYB risk segmentation frameworks
- Build and maintain dashboards and recurring reporting that provide visibility into rule effectiveness, operational efficiency, and overall risk exposure
- Perform ad hoc risk analyses across customer cohorts, geographies, products, and transaction behaviors to identify outliers or control gaps

## Requirements
- 2–4+ years of experience in risk analytics, financial crimes analytics, compliance data, fraud analytics, or related fields (fintech, banking, or payments preferred)
- Hands-on experience with blockchain intelligence tools such as **Chainalysis**, **TRM Labs**, **Elliptic**, or similar platforms
- Strong **SQL** skills (ability to write complex joins, aggregations, window functions, and performance-optimized queries on large datasets)
- Experience analyzing transaction-level data and building or optimizing rule-based monitoring logic
- Familiarity with **AML/BSA** concepts and transaction monitoring frameworks
- Ability to translate ambiguous regulatory requirements into structured, data-driven logic
- Strong analytical thinking and ability to independently structure open-ended problems

## Nice-to-Haves
- **Python** experience (**pandas**, **Polars**, or similar) for deeper analysis and automation
- Familiarity with KYC/KYB vendors (e.g., **Sumsub**, **Alloy**, **Persona**, etc.)
- Experience designing **Retool** workflows, internal tools, or compliance dashboards
- Exposure to card network data, ACH flows, wire transactions, or digital asset monitoring
- Experience supporting regulatory exams or external audits

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