Credit Risk Data Analyst

Seacoast National Bank•Saint Petersburg, FL

50d

About The Position

The Credit Risk Data Analyst is responsible for being an analytical leader in organizing and leveraging data to drive fact-based decisions and actions. The Credit Risk Data Analyst is responsible for developing and executing a consistent and coherent set of data and analyses for effective credit risk measurement and reporting across the bank. In addition to developing analytical insights, the incumbent must collaborate across the company for implementation, data management, analytical execution, forecasting, and on-going monitoring. The ideal candidate will possess finance, strategic and analytical acumen, and demonstrate the ability to collaborate with and to influence multi-functional team members across the bank.

Requirements

MA/MS in Statistics or Quantitative field preferred.
7+ years of progressive, related experience.
Strong analytic skills, knowledge of statistical software, and problem-solving ability are a must.
Knowledge in credit risk analytics, loan loss reserving process, loss forecasting, probability of default and risk rating development.
Provide attention to detail and ensure data accuracy.
Extensive programming skills with: SQL, SAS, Python, SAS/Stat, SAS Enterprise Miner, and/or R/Python.
Visualization software such as SAS Visual Analytics and Power BI.
Self-motivated to proactively learn and solve complex business problems.

Responsibilities

Synthesize credit data to provide analysis and conclusion for management, Board and Regulatory reports, including standard and ad-hoc requests, as needed.
Provide analytical insights for executive management and the board of directors on credit trends and emerging risks in portfolios.
Work with the analytics teams and data originators and users for consistency of use of data assets, as well as to eliminate redundancies and non-sanctioned variations.
Partner with lines of business to address root causes that create data quality issues.
Use analytical and technical skills for improving data quality and business insights, as well as influencing business process design.
Cultivate cross-functional relationships between business units to ensure insights become actionable and drive desirable business outcomes.
Utilize data handling and mining tools to support proactive data quality program focusing on business intelligence and analytics applications.
Standardize credit data definitions and classifications and ensuring that a data trail is effectively documented within the processes associated with accessing, retrieving, exchanging, reporting, managing, and storing of data.
Research data integrity issues when discrepancies are found. Run various reports to self-audit data and/or work with staff in the field to correct data as appropriate to ensure accuracy.
Lead resolution to external and internal audit inquiries and supporting documentation.
Proactively identify and evaluate emerging analytics software, technologies, and tools.