Senior Loan Data Associate
About The Position
We are seeking a highly analytical data professional to support our Loan Fund group through rigorous data analysis, business intelligence, and insight generation. This role will focus on loan-level and portfolio-level data to evaluate credit performance, risk trends, pricing, and profitability. The individual will leverage BI tools and statistical methods to transform complex loan data into actionable insights for senior leadership. The ideal candidate brings a strong background in data science or statistics, deep experience working with financial and credit data, and the ability to clearly communicate findings to technical and non-technical audiences.
Requirements
- Bachelor’s degree in Statistics, Data Science, Mathematics, Economics, Finance, or a related quantitative field
- Strong foundation in statistics and quantitative analysis
- 5+ years of experience in loan analytics, credit risk, financial analytics, or a related role
- Advanced SQL skills and experience working with large relational datasets
- Hands-on experience with BI platforms (Power BI, Tableau, Looker, etc.)
- Strong understanding of loan performance metrics and credit risk concepts
- Excellent written and verbal communication skills
Nice To Haves
- Master’s degree in Statistics, Data Science, Finance, or Applied Economics
- Experience with Python or R for statistical modeling and analysis
- Familiarity with CECL, stress testing, or regulatory reporting
- Experience working in banking, credit unions, fintech, or other regulated lenders
- Exposure to cloud data platforms and modern data stacks
Responsibilities
- Analyze loan-level and portfolio-level data across products (e.g., consumer, mortgage, commercial, indirect, HELOC)
- Evaluate credit performance, delinquency, charge-offs, prepayments, and loss severity
- Develop cohort, vintage, and roll-rate analyses to assess portfolio health
- Support stress testing, and scenario analysis efforts as applicable
- Identify emerging risk trends and performance outliers within loan portfolios
- Apply statistical and data science techniques (e.g., regression, forecasting, segmentation, survival analysis) to loan and credit datasets
- Develop analytical models to support underwriting, pricing, and portfolio strategy
- Test hypotheses related to credit performance, borrower behavior, and economic sensitivity
- Ensure analytical rigor, appropriate assumptions, and validation of results
- Design, build, and maintain dashboards and reports using BI tools (Power BI, Tableau, Looker, or similar)
- Partner with credit, finance, and lending leaders to define KPIs and performance metrics
- Automate recurring portfolio reporting and monitoring
- Ensure consistency and accuracy in data definitions and reporting outputs
- Translate complex analyses into clear, decision-oriented insights
- Prepare executive-ready presentations highlighting trends, risks, and recommendations
- Communicate findings to credit committees, senior management, and other stakeholders
- Provide data-backed recommendations that inform loan strategy and risk appetite
- Collaborate with data engineering, IT, and lending teams to source, clean, and structure loan data
- Support data governance, documentation, and audit readiness
- Improve data quality, transparency, and analytical repeatability
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
