Mortgage Analytics Developer - Fixed Income and Mortgages
The Mortgage Analytics Developer designs, builds, and maintains the loan-level analytics and simulation infrastructure used to support structured credit, mortgage, and asset-backed investment analysis. This role sits at the intersection of quantitative modeling, software engineering, and portfolio analytics, working closely with Research, Engineering, and Investment teams to transform collateral-level behavior into security-level insights.
This is a hands-on individual contributor role for someone who enjoys both modeling and software development, with responsibility spanning loan performance analytics, simulation frameworks, cash flow modeling, and desk-facing applications.
Core Responsibilities
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Develop and maintain loan-level simulation frameworks supporting mortgage and structured credit analytics.
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Build and enhance systems that transform collateral projections into cash flow, valuation, and risk analytics.
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Implement, validate, and maintain production-grade quantitative models used in investment and risk workflows.
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Analyze loan performance, collateral behavior, default trends, prepayment activity, and loss outcomes across structured products.
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Support portfolio managers, traders, and researchers through analytical tools, dashboards, and ad hoc investigations.
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Collaborate with quantitative researchers and data scientists to deploy and scale analytical models.
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Contribute to the ongoing improvement of pricing, surveillance, valuation, and risk infrastructure.
Required Qualifications
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Strong software engineering experience in Java or another object-oriented programming language, preferably within analytical or quantitative applications.
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Experience working with structured finance, mortgage, consumer credit, or securitized products analytics.
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Understanding of loan-level performance drivers including prepayments, defaults, delinquencies, transitions, recoveries, and loss severity.
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Advanced SQL skills and experience working with large-scale loan and collateral datasets in modern analytical data platforms.
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Experience implementing, validating, and supporting quantitative or econometric models in production environments.
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Strong software development discipline including testing, version control, code reviews, release management, and reproducibility.
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Ability to work directly with investment professionals and quantitative researchers in a fast-paced environment.
Preferred Qualifications
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Experience with RMBS, CMBS, ABS, CLO, consumer credit, residential mortgage, or commercial real estate collateral.
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Familiarity with structured finance cash flow models, securitization structures, waterfall mechanics, and security valuation.
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Experience with Python, PySpark, Scala, or distributed computing frameworks.
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Exposure to market and collateral data providers, loan-performance databases, and structured finance analytics platforms.
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Experience building scalable analytics services, distributed systems, or quantitative applications.
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Familiarity with machine learning workflows, model deployment, and production analytics environments.
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Experience using AI-assisted development tools for coding, testing, refactoring, and codebase exploration.
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Knowledge of cloud infrastructure, containerization, and modern application deployment practices.
Education
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Master's or PhD preferred in Computer Science, Financial Engineering, Statistics, Applied Mathematics, Economics, Physics, Engineering, or a related quantitative discipline.
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Strong candidates from other scientific or quantitative backgrounds with demonstrated software engineering and analytics experience will also be considered.
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Prior experience in structured credit, mortgage analytics, or related financial markets is preferred but not strictly required.
