Strategic Analytics - Associate

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.

Company