Fraud Data Scientist

In this role, you will be responsible for designing, developing, and deploying machine learning models to detect and prevent fraudulent activities, such as Merchant Fraud, transactional fraud, account takeover, and identity theft. You will work with large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity. Utilizing data analytics tools and methodologies, you will conduct in-depth assessments and generate fraud rules and reports on fraud trends, including first-party and third-party fraud. Collaboration with cross-functional teams, including risk management, operations, and compliance, will be crucial to enhance fraud prevention measures. Additionally, you will monitor industry trends, regulatory changes, and best practices to continually enhance fraud prevention strategies. Key Responsibilities: - Design, develop, and deploy machine learning models for fraud detection - Work with large datasets to identify fraudulent activity patterns - Utilize data analytics tools to conduct assessments and generate fraud reports - Collaborate with cross-functional teams to enhance fraud prevention measures - Monitor industry trends and regulatory changes for strategy enhancement Qualifications Required: - Bachelor's degree in engineering, technology, computer science, or related field - 3+ years of data analytics experience in fraud prevention or risk management - Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance - Strong experience in SQL or Python - Excellent communication and presentation skills - Detail-oriented with a proactive problem-solving mindset - Ability to work collaboratively in a cross-functional team environment,