Operations And Fraud Analytics Lead
Braviant Holdings
Job highlights
Summary
Join Braviant Holdings, Inc., a leading provider of tech-enabled credit products, as their Operations and Fraud Analytics Lead. Reporting to the Director of Credit Strategy, you will leverage advanced analytics to optimize business operations, develop fraud prevention strategies, and drive profitability. This role demands critical thinking, technical expertise, and collaboration across departments to solve complex business challenges. You will partner with various teams to develop data-driven strategies, analyze risk data, create reports, and develop forecasting models. The ideal candidate possesses 5+ years of experience in credit strategy, strong analytical skills, and proficiency in Excel, SQL, and Python. This position offers opportunities for professional growth within a fast-paced, high-growth company.
Requirements
- 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
- Bachelorβs degree (minimum) in Computer Science, Economics, Mathematics, Statistics, Engineering, Business Administration, or other quantitative-related fields
Responsibilities
- 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
Preferred Qualifications
- 3+ years of unsecured lending experience
- Results focus and leadership experience
- Experience working in a fast-paced, high growth startup
- 1 year of independently mining, organizing, analyzing and interpreting data
- Experience in unsecured lending is a plus
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