Credit Risk Analyst

We are seeking a highly skilled Credit Risk Data Analyst with strong SQL and SAS programming expertise to support credit risk reporting and analytics within a large financial institution. This role requires a hands-on “doer” who can manipulate, analyze, and extract insights from large datasets, as well as communicate findings to stakeholders. The ideal candidate has experience working in a large banking or financial services, with exposure to credit risk analytics preferred. Key Responsibilities 1. Reporting & Credit Risk Analysis • Develop and maintain monthly reporting for credit risk and portfolio performance. • Perform credit performance reviews, identifying trends, anomalies, and risk drivers. • Ensure accuracy, consistency, and timeliness of recurring reports. 1. Ad Hoc Analysis & Deep Dives • Conduct exploratory data analysis (EDA) to investigate business problems. • Define scope, extract relevant datasets, and perform deep-dive analysis. • Example: • Analyze declining loan/application approval rates • Identify drivers (e.g., credit score shifts, policy changes, segment performance) • Present actionable insights to stakeholders 1. Data Manipulation & Engineering • Extract, transform, and manipulate large datasets using SQL and SAS. • Perform data cleaning, validation, and transformation across multiple sources. • Work with structured and semi-structured data. 1. Stakeholder Communication • Translate complex data findings into clear business insights. • Present analysis results using Excel, dashboards, or presentations. • Collaborate with risk, product, and business teams. Required Qualifications • Technical Skills (Must-Have) • Advanced SQL skills (critical requirement): • Complex joins (INNER, LEFT, FULL) • Aggregations and groupings • Window functions (ROW\_NUMBER, RANK, LAG/LEAD) • Subqueries and Common Table Expressions (CTEs) • Data segmentation and dimensional analysis • Strong SAS programming experience: • Data step processing • PROC SQL • Data transformations and dataset merging • Strong experience with data manipulation and analysis • Proficiency in Excel for analysis and reporting • Domain Knowledge • Experience in banking or financial services Credit risk experience (highly preferred): • Credit policies, underwriting, or portfolio analysis • Risk metrics (default rates, approval rates, delinquency trends) Education • Bachelor’s or Master’s degree from a U.S.-accredited institution (preferred) • (e.g., Statistics, Mathematics, Finance, Economics, Computer Science) Preferred / Nice-to-Have Skills • Experience with large financial institutions or banks • Knowledge of data warehousing concepts • Exposure to data visualization tools (Tableau, Power BI) • Familiarity with Python/R for analytics • Experience with data scraping or ingestion techniques