United States onlyJob Title: Financial Crime Data Analyst (SQL & Large Data Sets)
Location: Remote (U.S.-based)
Job Type: Full-Time / Contract
About the Role:
We’re looking for a detail-oriented and highly analytical Financial Crime Data Analyst with expert-level SQL skills and experience working with large, complex datasets. This role is ideal for someone with a solid background in financial crime analytics, including Anti-Money Laundering (AML), Know Your Customer (KYC), and transaction monitoring.
As a fully remote member of a U.S.-based team, you'll be instrumental in analyzing financial data to uncover suspicious activity, support investigations, and ensure compliance with U.S. regulatory standards. Your insights will directly impact how we detect and prevent financial crime.
Key Responsibilities:
- Build and optimize complex SQL queries to analyze high-volume financial datasets
- Perform data-driven investigations related to AML, KYC, and transaction monitoring
- Translate analytical findings into actionable intelligence and regulatory reporting
- Collaborate with compliance, risk, and data engineering teams to support anti-financial crime initiatives
- Maintain compliance with U.S. financial regulations (e.g., BSA, OFAC, FinCEN)
- Uphold data governance standards and ensure data accuracy and integrity
Requirements:
- Advanced SQL skills, with a track record of working with large, high-complexity datasets
- Demonstrated experience in financial crime analytics (AML, KYC, transaction monitoring)
- Strong understanding of U.S. financial regulations and compliance frameworks
- Ability to interpret complex data and translate it into clear business insights
- Familiarity with data governance practices and regulatory reporting requirements
- Experience with BI/visualization tools (e.g., Tableau, Power BI) is a plus
What We Offer:
- 100% remote work within a U.S.-based team
- Competitive compensation and flexible working hours
- The opportunity to help combat financial crime and make a meaningful impact
United Kingdom
