Fraud Data Analyst

Role overview Investigate suspicious transactions and account activity to reduce fraud losses and protect customers. The analyst uses SQL and Python to find unusual patterns, document evidence, and improve prevention controls. The role requires careful judgment, clear communication, and comfort using AI tools in day-to-day work.

Responsibilities - Monitor transactions and accounts, identify suspicious behavior, and investigate potential fraud. - Use fraud detection tools and analytical methods to surface patterns and emerging threats. - Examine suspected cases, gather supporting evidence, and document findings clearly. - Query large datasets with SQL to detect anomalies and develop insights into fraudulent behavior. - Create and implement fraud rules, strategies, and controls. - Keep current with fraud methods, prevention practices, and detection technologies.

Requirements - At least two years of experience in fraud detection, prevention, or investigation, and at least two years working with SQL and Python. - Bachelor’s degree in a relevant area such as economics, computer science, or analytics. - Understanding of common fraud patterns, including account takeover, identity theft, and payment fraud. - Demonstrated experience with Claude or an equivalent large language model, and the ability to use AI for research, productivity, and communication. - Strong analytical skills, attention to detail, organization, and ability to manage multiple priorities independently and with a team. - Clear written and verbal communication, sound ethical judgment, and high integrity.

Nice to have Experience with fraud detection platforms and work in financial technology, payments, lending, banking, or financial services. A quantitative degree in statistics, mathematics, finance, or economics is preferred; graduate study is a plus.

Benefits and work setup The listing describes the position as full-time and remote. English-language resumes are required. The stated gross pay range is USD $2,900–$3,750 per month.