Fraud Data Analyst, Principal

Your Role

The Internal Audit Services team oversees the internal fraud detection program at Blue Shield. The Fraud Data Analyst Principal will report to the Director of Fraud Detection Technology and Investigations. In this role you will work closely with the Director to design and implement proactive fraud analytics for internal business owners across the enterprise to better identify and continuously monitor for potential internal fraud. This critical role will leverage advanced analytics, machine learning, and automation to identify, investigate, and mitigate potential fraud, waste, and abuse within our internal operations. This position requires a deep understanding of data analysis, fraud detection methodologies, and data science techniques, as well as proven leadership and communication skills. Experience in highly regulated industries is a plus.

Your Knowledge and Experience

• Bachelor's degree in a quantitative field such as Information Systems Management or a related field required
• Master's degree preferred
• Requires a minimum of 7 years of experience in fraud detection and analytics, with demonstrated experience in developing and implementing anti-fraud programs
• Ability to build and technically program fraud detection systems
• Extensive experience in programming languages such as SQL, Python and data visualization tools like Tableau, PowerBI, etc.
• Strong proficiency in data mining, statistical modeling, and rules-based analytics
• Proven ability to develop and implement automated fraud detection systems
• Excellent communication, presentation, and interpersonal skills, with a track record of effectively collaborating with executives and other business units
• Strong analytical and problem-solving abilities
• Ability to work independently and as part of a team
• Experience in the healthcare industry is highly desirable, demonstrating an understanding of healthcare related financial systems, compliance requirements and risk mitigation
• Fraud related certifications are strongly desired (e.g. CFE)