Systems Analyst, Debt

Overview

The Debt Asset Management Team is responsible for the oversight of a portfolio of commercial real estate debt investments. The Systems Analyst, Debt role is an exciting opportunity to leverage one’s knowledge of technology and business to drive delivery of business initiatives by bridging the gap between business requirements and technical solutions. This role will work closely with business stakeholders to analyze business needs and create scalable solutions.

This role will be a key driver in delivering technology-oriented solutions from design to deployment.

This role will be responsible for supporting the asset management team in preserving and creating value in the existing portfolio across various property types. The Systems Analyst, Debt will support the team by building technology-oriented solutions, contributing to data strategies, conducting complex financial analyses, authoring quarterly portfolio and asset level reports, and interacting directly with sponsors. In this role there will be tremendous learning and growth opportunities through interactions with leading experts in the real estate investment industry.

• Build, maintain, and improve data pipelines, implementations, and reporting workflows that support the asset management of commercial real estate debt investments across securitized and non-securitized portfolios, including CMBS, Conduit, SASB, CRE CLO, and other CRE debt structures.
• Develop Python and SQL based processes to ingest, clean, and warehouse data from servicing systems, remittance files, borrower reporting, property operating statements, rent rolls, market data, and internal portfolio management tools.
• Design data visualizations, reports, and analyses that connect information across the loan, property, tenant, borrower, deal, and bond levels to support surveillance, reporting, valuation, and asset-level decision-making.
• Implement workflow automation to improve the team’s ability to oversee large portfolios, identify outliers, and focus asset management attention on credits that require follow-up or deeper review. Partner closely with asset management professionals to translate real estate debt workflows into scalable tools and solutions.
• Utilize large language models (LLMs) to enhance data extraction, coding efficiency, process automation, and internal workflow design, with appropriate controls and human oversight.
• Support the loan onboarding and abstraction process, focusing on the abstraction of unstructured data fields from legal documents and underwriting materials so that debt investments can be efficiently monitored over time.
• Document process logic, business rules, system architecture, and workflow design so that tools are reliable, maintainable, and aligned with the needs of a real estate debt asset management platform.
• Continuously identify opportunities to improve the efficiency, scalability, and analytical depth of the Debt Asset Management Team.

• 0-2 years of relevant experience, including internships, research, or early-career work in data engineering, data science, computer science, quantitative analysis, or systems-focused roles.
• Strong proficiency in Python building data structures, implementing automation, and creating internal tools for business stakeholders.
• Working knowledge of relational databases, including the ability to structure, query, and maintain large datasets.
• Demonstrated ability to effectively utilize large language models (LLMs) in a project or business setting, with appropriate controls and human oversight.
• Interest in commercial real estate, real estate finance, structured credit, or fixed income investing, with a desire to learn how real estate debt portfolios are underwritten, monitored, and managed over time.
• Exposure to financial, operating, or asset-level data analysis through work experience, internships, project work, or coursework preferred; experience related to real estate, credit, lending, or investment analysis is a plus but not required.
• Ability and willingness to learn key real estate debt concepts such as property cash flow, leasing, collateral performance, loan structures,…