This SAS/SQL/Python Enterprise Fraud Risk Analyst position will support entity resolution (“link analysis”) and the supporting fraud research tool for the Enterprise Fraud Strategy team. This role requires partnership with the Enterprise Data Science team and engagement with the business lines to develop fraud mitigation strategies, evaluate emerging trends/attacks and protect against more complex orchestrated fraud. Solution is driven by connecting seemingly unrelated activity and requires advanced data, behavioral and predictive analysis. The ideal candidate is a self-starter who has analytical, technical, and business experience within the fraud prevention and detection domain.

Key Responsibilities

• Collaborate with business lines to understand First/Third-Party fraud landscape, build an on-going gap assessment, and determine emerging internal/external trends
• Partner with Enterprise Data Science to select, curate and transform large, complex data sets to support continued entity resolution and graph development (AI/ML techniques)
• Develop predictive fraud attributes and support integration within control environments.
• Develop policies and procedures used to evaluate and control for fraud risk
• Lead analytical projects with an emphasis on fraud risk using advanced analytical/statistical techniques and partnering with key stakeholders around the organization
• Proactively and strategically lead efforts to identify new risks to monitor, source data needed, and provide actionable recommendations based on reported results, benchmarks, and discovered patterns
• Ability to support and drive agile delivery of enterprise fraud initiatives
• Develop key reporting and on-going monitoring to track effectiveness of solution
• Maintain and manage the metadata / relationships for all external and internal data sources that are critical to the fraud analytical solution

Basic Qualifications

• Bachelor's or Masters’ degree, or equivalent work experience
• Seven to ten years of experience in risk management activities

Preferred Skills/Experience

• Bachelor’s degree in Business, Finance, Computer Science, Business Analytics, Statistics, or another quantitative field required
• SAS, SQL, R or Python experience
• Extensive data analytics experience preferably in the financial services industry
• Knowledge of financial services products, systems, and data preferably within the fraud domain
• Proficient computer skills, especially Microsoft Office applications and data analysis software
• Excellent presentation, interpersonal, written, and verbal communication skills
• Exceptional problem solving, critical thinking, and troubleshooting skills
• Ability to prioritize and manage multiple tasks, while establishing responsible deadlines
• Flexibility in day-to-day work and tolerance for ambiguity
• Positive ‘can-do’ attitude and a strong desire to continue to learn and ask questions
• The ability to work well in a team environment
• Ability to build relationships cross-functionally and over the phone
• Ability to work with and influence at all levels of the organization, including with senior leadership

• The role offers a hybrid/flexible schedule, which means there's an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days.