Credit Risk & Data Analyst

The Credit Risk Data Analyst is responsible for being strong analytical expert and leader in leveraging data, quantitative techniques, to drive fact-based decisions, and actions. The incumbent is responsible for developing and executing a consistent and coherent set of models and analytical tools for effective credit risk measurement, management and reporting across the bank. In addition to developing analytical tools, models and reports, the incumbent must collaborate with across the company for implementation, data management, model execution and analysis, forecast administration, and performance monitoring. The ideal candidate will possess extensive finance, strategic and analytical acumen, and demonstrate the ability to lead and influence multi-functional team members across the bank.

Duties and Responsibilities will include the following:

• Knowledge in Current Expected Credit Losses (CECL) loan loss reserving process, loss forecasting, probability of default and risk rating development.
• Partner with Accounting and other functions to ensure that credit risk models and analytics address both internal and regulatory requirements, such as Stress Testing and Allowance for Credit Loss accounting standards.
• Identify opportunities to improve business processes and decisions using data analytics.
• Lead team members in developing and implementing predictive analyses and models, visual/interactive reporting, segmentation analysis, and process automation. Identify the problem, provide potential solutions, and design the analysis or model construct.
• Provide attention to detail and ensure data accuracy.
• Present findings and follow-up with business partners and executive management to ensure results are implemented.
• Develop processes for analytical support and pricing for bank acquisitions and loan pool purchases.
• Lead resolution to external and internal audit inquiries and supporting documentation.
• Provide analytical insights to the executive management and board of directors on credit trends, including root cause analysis and potential solutions.
• Modeling data for automation rules in underwriting systems and portfolio management actions
• Proactively identify and evaluate emerging analytics software, technologies, and tools.
  
  

Qualifications:

• Strong quantitative and analytic skills, knowledge of statistical software, and problem-solving ability are a must.
• 10-15 years of progressive, related experience.
• MA/MS in Statistics or Quantitative field strongly preferred.
• CECL reserving methodology experience preferred
• Strong SAS programming skills, including SAS macro-language.
• SAS/Stat, SAS Enterprise Miner, and/or R/Python preferred.
• 5+ years of Statistical Modeling experience
• Visualization software such as Tableau or SAS Visual Analytics.
• Experience with Moody’s ImpairementStudio is beneficial.
• 5+ years prior Banking or Financial Services Experience Preferred
  
  

Other Skills:

• Self-motivated to proactively learn and solve complex business problems.
• Strong ability to explain complex subject matter to a non-technical audience.
• Strong attention to detail.
• Excellent communication, interpersonal, organization, and time-management skills.