Mortgage Analytics Developer - Fixed Income and Mortgages

Selby Jennings; New York (NY); On-site; USD 140,000 - 230,000; Full time

Job summary

Selby Jennings is seeking a Mortgage Analytics Developer to design, build, and maintain loan-level analytics and simulation infrastructure for fixed income and mortgages in New York. This hands-on role blends quantitative modeling with software development to transform collateral behavior into security-level insights.

You will work with Research, Engineering, and Investment teams, implementing production-grade models, analyzing loan performance, and delivering analytical tools and dashboards for

Qualifications

• Strong software engineering experience in Java or other OO language, with emphasis on analytical apps.
• Experience with structured finance analytics and mortgage-related datasets.
• Advanced SQL skills and large-scale data handling.
• Experience deploying, validating, and maintaining production-grade models.
• Knowledge of testing, version control, and reproducible software practices.
• Ability to work with investment professionals and quantitative researchers in a fast-paced env.

Responsibilities

• Develop and maintain loan-level simulation frameworks for mortgage analytics.
• Build systems converting collateral projections into cash flow and risk analytics.
• Implement and validate production-grade quantitative models.
• Analyze loan performance, delinquencies, prepayments, and loss outcomes.
• Support portfolio managers, traders, and researchers with analytical tools and dashboards.
• Collaborate with researchers to deploy scalable analytical models.
• Contribute to pricing, surveillance, valuation, and risk infrastructure improvements.

Skills

Java

SQL

Quantitative analytics

Software engineering

Model deployment

Collaboration with researchers

Education

Master's degree or PhD in a quantitative field

Tools

Python

PySpark

Scala

Spark

Docker

Kubernetes

Job description

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

• Develop and maintain loan-level simulation frameworks supporting mortgage and structured credit analytics.
• Build and enhance systems that transform collateral projections into cash flow, valuation, and risk analytics.
• Implement, validate, and maintain production-grade quantitative models used in investment and risk workflows.
• Analyze loan performance, collateral behavior, default trends, prepayment activity, and loss outcomes across structured products.
• Support portfolio managers, traders, and researchers through analytical tools, dashboards, and ad hoc investigations.
• Collaborate with quantitative researchers and data scientists to deploy and scale analytical models.
• Contribute to the ongoing improvement of pricing, surveillance, valuation, and risk infrastructure.

Required Qualifications

• Strong software engineering experience in Java or another object-oriented programming language, preferably within analytical or quantitative applications.
• Experience working with structured finance, mortgage, consumer credit, or securitized products analytics.
• Understanding of loan-level performance drivers including prepayments, defaults, delinquencies, transitions, recoveries, and loss severity.
• Advanced SQL skills and experience working with large-scale loan and collateral datasets in modern analytical data platforms.
• Experience implementing, validating, and supporting quantitative or econometric models in production environments.
• Strong software development discipline including testing, version control, code reviews, release management, and reproducibility.
• Ability to work directly with investment professionals and quantitative researchers in a fast-paced environment.

Preferred Qualifications

• Experience with RMBS, CMBS, ABS, CLO, consumer credit, residential mortgage, or commercial real estate collateral.
• Familiarity with structured finance cash flow models, securitization structures, waterfall mechanics, and security valuation.
• Experience with Python, PySpark, Scala, or distributed computing frameworks.
• Exposure to market and collateral data providers, loan-performance databases, and structured finance analytics platforms.
• Experience building scalable analytics services, distributed systems, or quantitative applications.
• Familiarity with machine learning workflows, model deployment, and production analytics environments.
• Experience using AI-assisted development tools for coding, testing, refactoring, and codebase exploration.
• Knowledge of cloud infrastructure, containerization, and modern application deployment practices.

Education

• Master's or PhD preferred in Computer Science, Financial Engineering, Statistics, Applied Mathematics, Economics, Physics, Engineering, or a related quantitative discipline.
• Strong candidates from other scientific or quantitative backgrounds with demonstrated software engineering and analytics experience will also be considered.
• Prior experience in structured credit, mortgage analytics, or related financial markets is preferred but not strictly required.