Data Scientist - Fraud Analytics

Job Description

Roles and Responsibilities: • Design, develop, and deploy machine learning models to detect and prevent fraudulent activities, such as Merchant Fraud, transactional fraud, account takeover, and identity theft • Work with large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity • Utilize data analytics tools and methodologies to conduct in-depth assessments and generate Fraud rules and reports on fraud trends (including first-party and third-party fraud). • Collaborate with cross-functional teams, including risk management, operations, and compliance, to enhance fraud prevention measures. • Monitor industry trends, regulatory changes, and best practices to continually enhance fraud prevention strategies. Skills Required: • Bachelor's degree in engineering, technology, computer science or related field. • 3+ years of proven data analytics experience in fraud prevention, risk management, or a related field • Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance. • Strong experience in developing Machine Learning models, Python and SQL. • Excellent communication and presentation skills with the ability to convey complex information clearly and concisely. • Detail-oriented with a proactive mindset toward problem-solving and risk mitigation. • Ability to work collaboratively in a cross-functional team environment.