Business Analyst (remote)

Mission Lane is a purpose-driven financial technology company dedicated to helping individuals build healthier financial futures through responsible credit solutions. The Principal Business Analyst, Fraud is responsible for developing and optimizing fraud prevention strategies that protect both customers and the organization while maintaining an exceptional customer experience.

Responsibilities:

• Design, develop, and implement fraud prevention strategies for application fraud and customer onboarding
• Continuously evaluate fraud controls to improve detection accuracy and reduce financial losses
• Balance fraud mitigation efforts with a seamless customer experience
• Identify vulnerabilities within application and risk processes and recommend strategic improvements
• Support the ongoing enhancement of enterprise fraud defense capabilities
• Analyze large datasets to identify emerging fraud trends, patterns, and suspicious activities
• Investigate fraud incidents to determine root causes and recommend preventive measures
• Evaluate fraud losses, risk indicators, and operational performance
• Develop actionable insights that improve fraud detection and operational effectiveness
• Monitor changing fraud techniques and recommend proactive countermeasures
• Utilize SQL, Python, and analytical tools to extract, analyze, and interpret business data
• Develop dashboards, reports, and performance metrics for fraud monitoring
• Track key performance indicators including fraud coverage, loss rates, defense effectiveness, approval rates, and operational performance
• Ensure data accuracy and integrity across analytical reports
• Present analytical findings to business stakeholders and executive leadership
• Design and execute A/B testing, Champion/Challenger testing, and other analytical experiments
• Measure the effectiveness of fraud prevention strategies through data-driven evaluation
• Optimize fraud rules and decision models based on analytical findings
• Recommend improvements that increase operational efficiency while minimizing customer friction
• Support continuous enhancement of fraud decisioning processes
• Partner with Operations, Product, Data Science, Engineering, and Risk teams to develop fraud solutions
• Collaborate on new product initiatives and customer experience improvements
• Translate complex analytical findings into practical business recommendations
• Support enterprise projects focused on fraud prevention and operational excellence
• Build strong working relationships across multiple business functions
• Identify opportunities to improve fraud operations, workflows, and decision-making processes
• Analyze business requirements and recommend technology-driven solutions
• Develop business cases supporting new fraud initiatives
• Support implementation of process improvements and operational enhancements
• Promote best practices for fraud analytics and business intelligence
• Prepare executive-level reports and performance dashboards
• Monitor fraud strategy performance against organizational objectives
• Present findings, recommendations, and performance updates to stakeholders
• Ensure timely reporting of fraud metrics and business outcomes
• Support leadership with data-driven strategic planning

Requirements:

• Bachelor's or Master's degree in Economics, Finance, Engineering, Mathematics, Statistics, Data Analytics, or a related quantitative field
• Three or more years of experience in business analytics, risk management, fraud analytics, data science, or a similar analytical role
• Experience analyzing credit card, consumer lending, or financial services data
• Hands-on experience designing and executing A/B testing or Champion/Challenger testing methodologies
• Strong analytical, quantitative, and problem-solving abilities
• Experience using SQL, Python, or other data analysis tools
• Excellent written, verbal, and presentation communication skills
• Proven ability to independently solve complex business problems from analysis through implementation
• Direct experience in fraud strategy, fraud analytics, or financial crime prevention
• Advanced proficiency with SQL and Python
• Experience working within fintech, banking, consumer lending, or financial services
• Experience supporting high-growth or startup environments
• Knowledge of fraud detection models, risk management frameworks, and customer lifecycle analytics
• Experience developing executive dashboards and business intelligence reporting