Operations and Fraud Analytics Lead

Who we are: Founded in 2015 and based in Chicago, IL, privately held Braviant Holdings, Inc is a leading provider of tech-enabled credit products which combine breakthrough technology and cutting-edge machine learning to transform how people access credit online. The Company’s next-generation approach to lending reduces credit barriers and creates a Path to Prime® helping millions of underbanked consumers build credit history, reduce their cost of borrowing, and take control of their personal finances. Braviant has been named multiple times to the Inc. 5000 list of fastest growing private companies and has been recognized as a Best Place to Work.

The Role:Reporting to the Director of Credit Strategy, the Operations and Fraud Analytics Lead role is a compelling opportunity for a data-driven professional with a strong background in risk analysis and operational strategy. The successful candidate will leverage advanced analytics to optimize business operations, develop fraud prevention strategies, and drive profitability across Braviant’s operations. This role requires a combination of critical thinking, technical expertise, and the ability to collaborate across departments to identify, mitigate, and solve complex business challenges.

What You’ll Be Doing:

• Partner with the call center / ops senior leadership to develop data-driven strategies to create business value in the call center value chain.
• Analyze and interpret risk data using a variety of techniques, ranging from simple data aggregation to complex data mining. Documents findings, presents and submits data-driven and analytics-based recommendations to Senior Management.
• Compile reports, charts, and tables based on established analytical methods related to key operational performance metrics.
• Develop and monitor forecasting models; complete monthly/quarterly trend analysis; conduct on-going sensitivity analysis to optimize business recommendations.
• Collaborate with Operations, Marketing and Technology to make necessary changes on projects to drive business growth.
• Work with Operations and Risk Leadership to improve collection strategies with data driven decisions and onboarding new vendors to improve recoveries.
• Analyze large volumes of financial data to identify patterns, trends, and anomalies that indicate fraudulent activities. Use data modeling and statistical analysis to detect suspicious activities and unusual transactions.
• Work with Operations and Risk Leadership to develop and implement fraud prevention strategies using data analytics and implementing fraud detection tools.
• Collaborate with Operations, Marketing, and Technology teams to implement necessary changes on projects that drive business growth.
• Prepare detailed reports documenting findings on fraud investigations and work with senior management to take actions to reduce fraud.
• Make business recommendations for monitoring fraud and changing underwriting policies to mitigate fraud risk.
• Assist with onboarding new data tools to combat potential fraud while analyzing the opportunity costs of declines that may not necessarily be fraudulent, balancing risk mitigation with profitability.

What you'll bring:

Key Competencies- Critical Thinking: Leverages logic and reasoning to evaluate the strengths and weaknesses of alternative solutions, conclusions, or approaches to problems.

• Problem Solving: Identifies and resolves issues promptly; gathers and analyzes information effectively; develops innovative solutions; collaborates well in group problem-solving situations.
• Business Acumen: Understands the implications of business decisions; aligns work with strategic goals; demonstrates a strong focus on profitability and growth.

Qualifications and Experience- Professional Experience: 5+ years of experience managing credit strategy, preferably in consumer lending, with a focus on business growth, profitability, and financial performance.

• Strong understanding of credit risk and fraud management, utilizing both traditional and alternative credit data.
• Technical Skills: Advanced proficiency in Excel for data storytelling and predictive modeling.
• Working knowledge of SQL and Python, with the ability to read and adapt data models for output.
• Familiarity with Microsoft Office and Google Suite applications.
• Communication Skills: Exceptional verbal and written communication skills, with meticulous attention to detail.
• Project Management: Proven ability to manage multiple projects simultaneously and deliver end-to-end results, either individually or through a small team.

Education- Bachelor’s degree (minimum) in Computer Science, Economics, Mathematics, Statistics, Engineering, Business Administration, or other quantitative-related fields.