Fraud Strategy - Risk Analyst II - P2

About the role

As a member of the Acquisition Fraud Strategy team within the Risk Management department, the Risk Analyst II will develop, implement, and evaluate fraud risk strategies that reduce losses, improve profitability, and increase efficiency, while maintaining a superior customer experience. This individual contributor role works alongside peers to detect and prevent fraud loss associated with high-risk transactional activity.

Responsibilities

• Develop, implement, and evaluate fraud risk strategies.
• Analyze and present data in easy-to-understand visualizations and recommendations appropriate to the type of activity under review.
• Apply industry best practices and provide standards for solution, execution, and delivery approach.
• Utilize analytical and quantitative skills by using data and metrics to test theories, confirm assumptions, generate insights/recommendations, and measure success.
• Manage multiple projects under tight deadlines.
• Provide analytics and insights to organizational leaders in response to their business questions using data, tools, technologies, and discovery solutions.
• Create and maintain strategy and procedural documentation.
• Utilize business acumen to transfer knowledge of emerging fraud trends to data analysis and subsequent real-time transactional rule creation.
• Employ strong analytical thinking and coding skills (Python, R, SQL, SAS Enterprise Guide, or similar data analysis tool) to investigate transaction details and build loss mitigating strategies.
• Interact and collaborate with various cross-functional business partners such as Operations, Compliance, Modeling, and Technology teams.
• Monitor the performance of fraud risk strategies to ensure an optimal balance between risk and customer experience.

Requirements

• Bachelor’s degree in Economics, Decision Sciences, Mathematics, Statistics, Computer Science, or a related quantitative field.
• 2-4 years of work experience in a similar role in a professional corporate environment.
• Ability to transform big data into recommended actions to prevent fraud loss.
• Proficiency in Python, R, SQL, SAS Enterprise Guide, SAS Enterprise Miner, or a similar programming language is required.
• Strong critical thinking, problem-solving, analytical, and quantitative skills.
• Ability to drive and influence business decisions based on metrics and data.
• Demonstrated ability to simplify complex topics for broad audiences.
• Knowledge of fraud and credit risk analysis, along with an understanding of profitability drivers, financial analysis, and credit reporting.
• Experience in identifying and preventing fraud risk and/or experience in developing and/or using fraud risk models, algorithms, or scorecards.
• Works well within a collaborative team environment.
• Excellent verbal and written communications skills.
• Collaborative team player with the ability to effectively manage competing priorities.

Preferred Qualifications

• Master’s Degree in a related field.
• Experience with creating strategies within a fraud decision engine.