We are seeking a skilled Fraud Data Analyst to analyze transaction data, detect potential fraud, and enhance risk mitigation strategies across the organization.
Key Responsibilities:
Analyze transaction data for fraud detection: Perform in-depth analyses of transaction data to identify patterns indicative of fraud.
Develop and maintain fraud detection models: Build predictive models to detect fraudulent behavior in real-time using machine learning and data analytics tools.
Collaborate on risk assessment and prevention strategies: Work closely with risk management teams to design fraud prevention strategies.
Conduct root cause analysis on fraud incidents: Investigate fraudulent activities to understand their origins and impacts.
Create and maintain fraud detection dashboards: Design and maintain dashboards using tools like Tableau or Power BI to provide real-time monitoring of fraud metrics.
Requirements:
Fraud analysis and pattern recognition: Strong ability to detect patterns, anomalies, and indicators of fraud in data.
Predictive modeling and machine learning: Experience building models for fraud detection using supervised and unsupervised learning techniques.
Risk assessment and prevention: Understanding of risk management principles and strategies for fraud prevention.
Data visualization and reporting: Proficiency in data visualization tools like Tableau, Power BI, or Looker for creating dashboards and presenting fraud data to stakeholders.
Benefits:
Comprehensive medical, dental, and vision insurance plans.
Creative vacation, sick leave, and 20 paid holidays per year.
Flexible work schedules and telecommuting options.
Opportunities for training, certification reimbursement, and career advancement programs.
Key Skills:
data visualization tools like Tableau, Power BI, or Looker for creating dashboards and presenting fraud data to stakeholders. BI Analyst, Microsoft SQL, Python
