Fraud Data Analyst

Fraud Analytics

• Design and implement predictive fraud detection models using machine learning techniques to uncover suspicious behavior and patterns.
• Continuously improve fraud monitoring systems to enhance detection precision while minimizing false alarms.
• Evaluate both internal and external datasets to identify weaknesses and suggest preventive strategies.
• Establish and monitor key performance indicators to gauge the effectiveness of fraud detection efforts.

Market Intelligence

• Keep abreast of new fraud methods, industry standards, and regulatory updates.
• Conduct competitor risk management analysis to discover areas for enhancement.
• Deliver actionable insights from market intelligence to guide strategic planning.

Team Leadership

• Recruit, develop, and lead a skilled team comprising data analysts, scientists, and market intelligence experts.
• Collaborate effectively with teams in risk management, compliance, IT, and other units to ensure cohesive communication and alignment.

Qualifications

Education

• Master's degree in Data Science, Statistics, Economics, Business Administration, or related disciplines.

Experience

• Over 10 years of professional experience in fraud analytics, risk management, or data analysis.
• Demonstrated success in creating and deploying fraud detection systems.
• Experience utilizing market intelligence tools and conducting competitive evaluations.

Technical Skills

• Proficiency with data analytics software such as Python, R, SQL, and SAS.
• Knowledgeable in machine learning frameworks and fraud detection technologies.
• Understanding of relevant industry regulations and compliance requirements.

Key Competencies

• Strong analytical and problem-solving capabilities.
• Effective leadership and team management skills.
• Strategic mindset combined with solid business insight.
• Clear communication skills to translate complex data findings for broader audiences.