Selby Jennings
Selby Jennings

Mortgage Analytics Developer - Fixed Income and Mortgages

• Posted 3 days ago • Updated 3 days ago
Full Time
On-site
Fitment

Dice Job Match Score™

🛠️ Calibrating flux capacitors...

Job Details

Skills

  • Fixed Income
  • Investment Analysis
  • Research
  • Modeling
  • Dashboard
  • Collaboration
  • Pricing
  • Surveillance
  • Java
  • Object-Oriented Programming
  • SQL
  • Analytical Skill
  • Software Development
  • Version Control
  • Release Management
  • Cash Flow
  • Securitization
  • Waterfall
  • Mechanics
  • Valuation
  • Python
  • PySpark
  • Scala
  • Distributed Computing
  • Database
  • Machine Learning (ML)
  • Workflow
  • Artificial Intelligence
  • Testing
  • Code Refactoring
  • IaaS
  • Computer Science
  • Computational Finance
  • Statistics
  • Applied Mathematics
  • Economics
  • Physics
  • Software Engineering
  • Mortgage
  • Analytics
  • Finance

Summary

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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90922487
  • Position Id: 24666370
  • Posted 3 days ago
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