Enterprise Fraud Portfolio Analytics & Strategy Analyst

• Code and deploy fraud strategies to mitigate fraud losses
• Provide financial and regulatory reporting and analyses
• Maintain adequate controls over financial and regulatory reporting processes
• Run complex business performance, risk, and operational analytics
• Develop analytical methods and models to assess market, credit, and operational risk
• Analyze large datasets to improve risk-adjusted returns and deliver profitable growth
• Communicate analytical conclusions and recommend and implement business strategies
• Improve lending decisions, manage risk, increase revenues, reduce loss exposure, meet business goals, and improve performance
• Establish strategy baselines and track actual performance against expectations
• Apply predictive models, third-party data, and other tools for segmentation and targeting
• Manage engagements with internal and external information suppliers
• Work with business, credit, data, and model development partners to design, develop, and monitor tests and analytical reporting
• Design and enhance standard reporting suites for product and portfolio reviews
• Collaborate with line of business, Finance, and Risk partners to assess and establish credit risk appetite and related policies and procedures

• SQL, R, Python, Power Automate, PowerBI, and data science skills
• Understanding of Boolean logic
• Fraud experience in deposits, digital, new account origination, and/or card fraud
• Strong analytical skills
• Ability to work longer or off hours if needed during a fraud incident
• No employment visa sponsorship or STEM OPT participation
• 2+ years of relevant professional experience
• University/college degree, typically; a comparable combination of education, job-specific certifications, and experience may be considered in lieu of a degree
• Bachelor's degree
• No required certifications
• No required licenses

Demonstrates expertise in fraud strategy development and implementation, utilizing advanced analytical methods and tools such as SQL, R, and Python to enhance risk management and financial reporting processes. Proven ability to analyze large datasets for improved decision-making and performance tracking.

• SQL
• R
• Python
• Fraud Experience
• Analytical Skills

• Data Science Skills
• Predictive Modeling
• Business Performance Analytics
• Risk Analysis
• Financial Reporting

• Communication Skills
• Collaboration

• Fraud Mitigation
• Credit Risk
• Operational Risk
• Regulatory Reporting
• Market Risk

• Power Automate
• PowerBI