Fraud Data Scientist

The role involves designing, developing, and deploying machine learning models to detect and prevent fraudulent activities, including Merchant Fraud, transactional fraud, account takeover, and identity theft. You will be working with large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity. Using data analytics tools and methodologies, you will conduct in-depth assessments and generate Fraud rules and reports on fraud trends, both first-party and third-party fraud. Collaboration with cross-functional teams, such as risk management, operations, and compliance, is essential to enhance fraud prevention measures. Monitoring industry trends, regulatory changes, and best practices will be necessary to continually improve fraud prevention strategies. The ideal candidate should have a Bachelor's degree in engineering, technology, computer science, or a related field, along with at least 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 is required. Strong experience in SQL or Python is essential. Excellent communication and presentation skills are crucial, with the ability to convey complex information clearly and concisely. The candidate should be detail-oriented with a proactive mindset towards problem-solving and risk mitigation. Additionally, the ability to work collaboratively in a cross-functional team environment is key.,