Sherwayne Allen

AML investigations professional with 2 years of experience conducting risk-based investigations into money laundering, terrorist financing, and financial crime at a FinCEN-regulated crypto-asset exchange. Skilled in gathering intelligence from multiple sources to determine reasonable grounds to suspect (RGS), investigating complex and high-risk cases referred through transaction monitoring and media scanning, and maintaining accurate, contemporaneous investigative records. Strong foundation in AML frameworks and regulatory requirements, with Chainalysis and TRM Labs blockchain analytics certifications supporting complex case analysis.

AI/ML Project Contributor (Unpaid Practicum) at Lighthouse — Music Startup AI (2025-08 – 2026-04)

• Built end-to-end PyTorch LSTM prediction platform served via Dockerized Flask REST API with automated feature engineering and walk-forward validation ensuring model reliability over time.
• Engineered real-time data ingestion pipeline integrating Songstats API with WebSocket analytics dashboard; maintained sub-second prediction latency in live production environment.

KYC/AML Analyst at FTX.US — Crypto-Asset Exchange (2021-05 – 2023-02)

• Identified fraud patterns and trends, escalating findings to appropriate business partners and collaborating with the compliance team to share information for fast, coordinated action.
• Coordinated with law enforcement agencies on financial crime investigations, producing audit-ready case documentation suitable for regulatory examination.
• Filed Suspicious Activity Reports with 100% regulatory compliance — conducting OFAC/PEP screening, criminal name checks, and high-risk account escalation while adhering strictly to AML/ATF policies and FinCEN regulatory requirements.
• Reviewed KYC documentation at account opening and ongoing monitoring stages across 300+ daily reviews, applying OFAC/PEP screening and sanctions risk assessment to identify reportable activity.
• Gathered information and intelligence from all available sources to determine reasonable grounds to suspect (RGS) money laundering, terrorist financing, or other criminal activity — planning and completing risk-based investigations into matters referred through transaction monitoring and internal escalations across 200+ cases.
• Communicated investigation findings and risk assessments to compliance leadership and cross-functional stakeholders, translating technical case analysis into clear, actionable summaries.

Diploma in Software Engineering — Artificial Intelligence – Centennial College (2023-09 – 2026-04)

B.S. in Mathematics – Auburn University (2021)