Senior Fraud Data Analyst X2

Sr. Fraud Data Analyst

W2 - GC/USC only - No Sponsorship provided

Tampa, FL - Remote

The Senior Fraud Analyst participates actively in the Credit union’s fraud prevention and risk management activities to mitigate both the credit union and our members exposure to potentially fraudulent activities. The position is responsible for evaluating member and situational/threat trends by channel, as well as cross-channel. Performs ongoing analytics and prepares recommendations which are presented to first line VP’s and SVP’s enterprise wide. The senior analyst leverages state-of-the-art industry data sciences tools to synthesize and analyze data; create recommendations and respond to fraud attacks. In addition, Senior fraud analysts will also help develop new fraud risk reporting utilizing business intelligence. Must have - Structured Query Language (SQL), Python, Spark, R, and SSRS report writing to be considered.

Responsibilities

Develop and produce executive key performance metrics to report to senior management and enterprise risk team

Utilize business intelligence to develop new methods for fraud risk reporting

Develop analytics and make recommendations for enterprise fraud strategies to minimize fraud loss

Assess fraud trends and provide real-time recommendations to mitigate potential fraud for the credit union and its members.

Perform complex analysis and modeling to identify patterns of fraudulent transactions and create prevention methods

Create, test, and implement rule criteria in applicable detection systems (FIS, Falcon, Verafin, Alloy etc.)

Balance fraud prevention recommendations with member experience considerations

Analyze loss data to recommend and implement appropriate loss prevention strategies

Evaluate fraud cases and losses holistically to identify areas of improvement

Create and deliver BI reporting to develop thorough reporting for senior leadership, boards, and examiners

Maintain knowledge and understanding of current trends, laws, and issues affecting the area of expertise

Attend educational events to increase professional knowledge

Qualifications

Bachelor’s degree in business administration, finance, computer science, risk management, or a related field (A comparable combination of work experience and training may be substituted for education requirements)

6+ years of data analysis experience, preferably with a financial institution

5+ years of Structured Query Language (SQL), Python, Spark, R, and SSRS report writing required

4+ years of experience with Business Intelligence tools such as PowerBI, Tableau, Qlik required

4+ years in fraud analytics required

Strong knowledge of descriptive and predictive statistical tools

Excellent verbal, written, and interpersonal communication skills to effectively communicate with team members and external stakeholders

Excellent presentation skills to communicate complex results to business audiences not familiar with data and analytics

Ability to prioritize tasks, deal effectively with competing and changing priorities to meet deadlines

Accurate, detail-oriented, and organized with task management

Strong analytical and problem-solving skills with the ability to interpret large amounts of data

Skills

AI & Machine Learning

Analytics

Data Science

Project Management