• Aggregate data from multiple sources to provide a comprehensive assessment.
• Conduct data mining studies such as profiling, segmentation, or vintage analysis to identify and understand the sources of risk to limit risk exposure or take certain risks to generate returns.
• Analyze data to better understand potential risks, concerns, and outcomes of decisions.
• Recommend credit/champion-challenger programs, if feasible.
• Collaborate with other team members to effectively analyze and present data.
• Create reports, summaries, presentations, and process documents to display results.
• Develop, recommend, implement, and evaluate strategies to support tactical decision-making by determining the root cause of the issue through analysis, awareness of business trends, or leading questions from management.
• Develop and review early warning triggers in line with risk appetite for both new acquisition, portfolio, and collections and ensure periodic validation of the trigger for optimal profitability through the economic cycle.
• Collaborate regularly with stakeholders to ensure strategies are timely, relevant, and actionable.
• Generate portfolio monitoring MIS/dashboards, analyze, and highlight to management any emerging risk and opportunities such as through-the-door, vintage analysis, coincident and lagged delinquencies, credit limit increase/decrease performance, as well as results of risk studies and credit tests conducted,
• Analyze credit metrics and recommend improvements on credit strategies and/or processes.
• Analyze collection metrics and recommend improvements on collection strategies and/or processes; and
• Develop collection and recovery strategies using data on behavior, demographics, and emerging view of portfolios.
• Assist in driving project(s) and closely collaborate with project teams.
• Supervise, train, and guide junior risk analysts on credit risk management and analytics.
  
  

• Bachelor’s Degree in Statistics, Mathematics, Economics, Data Science, or Engineering
• At least 3 years experience in Data Management, Data Engineering, Risk Modeling/Data Science, Credit risk management, Collections, Fraud, Data science/analytics or related disciplines in a consumer lending industry
• Proficient in data/analytical tools, e.g., SAS, Python, VBA, Tableau, etc. and any credit, collections or fraud systems
• Analytical and good problem-solving skills
• Excellent written and oral communication skills with distinct ability to convey complex data in a concise understandable manner

Please refer to job description.