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Key Functions/ Basic Duties:
- Analyze transactional and post-transactional data to detect and assess fraud trends, patterns, and anomalies.
- Perform dispute analytics for decision engine feedback and fraud strategy implementation requirements.
- Utilize tools such as SQL, Power BI, and other data visualization/analysis platforms to generate actionable insights.
- Record discrepancies between existing controls and the level of risk protection required, highlighting areas where enhancements are needed.
- Configure and optimize fraud rules within our card processor’s fraud platform to mitigate fraudulent events in real time.
- Identify and address general risks related to device security and website vulnerabilities, incorporating these insights into fraud prevention strategies.
- Collaborate with cross-functional teams, including compliance, IT security, customer service, and dispute resolution, to ensure seamless fraud prevention processes.
- Stay informed about industry trends and emerging fraud schemes to adapt strategies proactively.
- Create and deliver regular fraud reports and recommendations to stakeholders.
- Develop and maintain documentation of fraud prevention procedures, rule configurations, and response plans.
Knowledge/Skills/Abilities:
- Proven experience managing and leading a team, with a focus on fostering growth and driving results.
- Proficiency in SQL, Power BI, and other data analysis tools; experience with Python or R is a plus.
- Familiarity with industry decision engine tools and capabilities to drive real-time and near real-time decision making while incorporating feedbacks.
- General understanding of risks associated with devices, websites, and online transactions.
- Strong analytical skills with the ability to interpret complex data and create actionable insights.
- Demonstrated ability to lead fraud mitigation efforts and implement data-driven solutions.
- Excellent communication and presentation skills for reporting findings and collaborating with stakeholders.
- Knowledge of regulatory compliance frameworks (e.g., AML, BSA, UDAAP) is preferred.
- Strong self-confidence, good judgment, and the ability to make sound decisions
- Advanced knowledge of Word, Excel, PowerPoint, and Power BI is required
- Intermediate/advanced knowledge of SQL, DAX, Power Automate, and Analysis Services preferred
Education and/ or Experience:
• Bachelor’s degree in Business, Finance, Data Science, or a related field (or equivalent experience), preferred.
• Minimum of 3–5 years of experience in fraud prevention, data analysis, or risk management in the financial services or payments industry.
Language Skills: Fluent in English
Computer Skills:
- MS Office with a high level of proficiency with Excel.
- Proficiency in SQL, Power BI, and other data analysis tools; experience with Python or R is a plus.