Description:

The Fraud Data Analyst will analyze transaction data to detect potential fraud and enhance risk mitigation strategies across the organization.
This role involves working with fraud prevention teams, data scientists, and risk management to develop models and implement fraud detection strategies.
Key responsibilities include performing in-depth analyses of transaction data to identify patterns indicative of fraud, using statistical methods to spot anomalies, and flagging suspicious activities for further investigation.
The analyst will build predictive models to detect fraudulent behavior in real-time using machine learning and data analytics tools.
Collaboration with risk management teams is essential to design fraud prevention strategies and provide insights on vulnerabilities.
Conducting root cause analysis on fraud incidents to understand their origins and impacts is a critical part of the role.
The analyst will create and maintain fraud detection dashboards using tools like Tableau or Power BI for real-time monitoring of fraud metrics.
Implementing data-driven rules and alerts for flagging suspicious activities and establishing automated alerts for faster responses to potential fraud cases is required.
Staying updated on the latest trends in fraud schemes, methodologies, and detection technologies is necessary to bring innovative strategies to improve fraud prevention and detection.

Requirements:

Strong ability to detect patterns, anomalies, and indicators of fraud in data, with familiarity in transaction data analysis and fraud detection techniques.
Experience in building predictive models for fraud detection using supervised and unsupervised learning techniques, with familiarity in tools like Python, R, or SQL.
Understanding of risk management principles and strategies for fraud prevention, with the ability to recommend preventive actions based on data insights.
Proficiency in data visualization tools like Tableau, Power BI, or Looker for creating dashboards and presenting fraud data to stakeholders.
Excellent communication skills for collaborating with cross-functional teams and explaining complex fraud patterns to non-technical audiences.
A Bachelor’s or Master’s degree in Data Science, Statistics, Business Analytics, Finance, or a related field is required, with equivalent experience in fraud analytics or risk management considered.
Certifications in fraud examination or analytics, such as Certified Fraud Examiner (CFE) or Certified Analytics Professional, are advantageous.
A minimum of 3 years of experience in fraud analysis, risk management, or data analytics, with a proven track record of detecting and preventing fraudulent activities is required.
Familiarity with financial services, e-commerce, or insurance fraud detection is highly beneficial, along with experience in real-time data processing and anomaly detection.

Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums are provided.
Competitive vacation, sick leave, and 20 paid holidays per year are included in the paid time off policy.
Flexible work schedules and telecommuting options promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs support professional development.
Access to wellness programs, including gym memberships, health screenings, and mental health resources is available.
Life insurance and short-term/long-term disability coverage are part of the life and disability insurance benefits.
Confidential counseling and support services for personal and professional challenges are offered through the Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development is provided through tuition reimbursement.
Opportunities to participate in community service and volunteer activities are encouraged for community engagement.
Employee recognition programs celebrate achievements and milestones within the organization.