As aStrategic Analytics - Associatein theDigital Fraud Strategyteam, you will play a critical role in protecting our customers and the firm from emerging fraud threats across digital payment channels such as Zelle, bill pay, wire transfers, ACH, funds transfers, and real-time payments. You will own the end-to-end process of fraud loss management, leveraging advanced analytics, machine learning, and innovative strategies to identify trends, reduce losses, and enhance the customer experience. This role offers the opportunity to work with large, complex datasets, collaborate with cross-functional teams, and present actionable insights to senior leadership, all while developing your skills in a dynamic and fast-paced environment.

Job Responsibilities

• Analyze large and complex datasets to uncover trends and behaviors in digital fraud activity.
• Develop and implement creative, data-driven strategies and business rules to reduce fraud losses.
• Monitor fraud trends and proactively identify emerging risks and vulnerabilities.
• Design and automate processes to improve the efficiency and effectiveness of fraud alert systems.
• Collaborate with technical and business partners to develop and implement new fraud-fighting products using agile methodologies.
• Communicate complex analytical findings and strategies clearly to both technical and non-technical audiences, including senior leadership.
• Simplify and present data-driven insights in concise presentations and reports.
• Work closely with cross-functional teams to address points of friction and enhance the customer experience.
• Respond rapidly to emerging fraud issues and adapt strategies as needed.
• Apply strong problem-solving skills to develop elegant and practical solutions to complex business challenges.
• Maintain a strong understanding of P&L drivers and the financial impact of fraud strategies.

Required Qualifications, Capabilities, and Skills

• Minimum 2 years of professional experience in analytics, risk management, or data science.
• Proven ability to analyze and interpret large datasets and translate findings into actionable business strategies.
• Proficiency in analytical programming languages such as Python, SAS, R, or SQL.
• Advanced skills in Excel and PowerPoint for data analysis and presentation.
• Strong communication skills with the ability to convey complex data and concepts clearly.
• Demonstrated experience in designing and analyzing experiments.
• Ability to develop concise presentations with sound business conclusions.
• Strong critical thinking and intellectual curiosity.
• Experience working collaboratively within teams and across functions.
• Ability to manage diverse tasks and respond to rapidly changing priorities.
• Passion for problem-solving and continuous improvement.

Preferred Qualifications, Capabilities, and Skills

• Experience in digital payments, fraud prevention, or financial services.
• Familiarity with machine learning models and their application in fraud detection.
• Experience with agile project management methodologies.
• Strong understanding of drivers of profitability and P&L management.
• Track record of developing and implementing new products or analytical solutions.
• Experience with vendor and in-house data integration.
• Ability to brainstorm and implement solutions to improve customer experience and reduce complaints.