Mortgage Analytics Developer

Selby Jennings; New York (NY); On-site; USD 140,000 - 240,000; Full time

Job summary

Selby Jennings seeks a Mortgage Analytics Developer in New York focused on fixed income and mortgages. The role combines quantitative modeling, software engineering, and portfolio analytics to transform collateral behavior into security‑level insights.

You will develop loan‑level analytics, build cash flow and risk metrics, and support prepayment and default modeling in a fast‑paced investment environment.

Qualifications

• Strong software engineering experience in an object‑oriented language (Java/C++).
• Hands-on INTEX implementation experience required (not just using INTEX outputs).
• Experience with RMBS/CMBS/ABS/CLOs or mortgages/structured finance.

Responsibilities

• Develop and maintain loan‑level mortgage and structured credit analytics.
• Build systems transforming collateral projections into cash flow, valuation, and risk metrics.
• Support prepayment, default, delinquency, recovery, and loss modeling workflows.
• Design and maintain analytical tools for portfolio managers, traders, and researchers.
• Enhance pricing, surveillance, valuation, and risk infrastructure.
• Deploy and support production quantitative models.

Skills

Java/C++ programming

INTEX implementation

SQL

Tools

INTEX API

INTEXCalc

Cash flow engine

CMO subroutines

Job description

Mortgage Analytics Developer - Fixed Income and Mortgages

Our client is a highly respected New York-based alternative asset manager focused on structured credit, mortgages, and asset-backed investments. The team combines deep fundamental credit expertise with sophisticated quantitative analytics and technology, providing direct exposure to portfolio managers, researchers, and investment decision-making while building critical analytics infrastructure used across the investment platform.

The Mortgage Analytics Developer designs and maintains loan-level analytics, simulation, cash flow, valuation, and risk infrastructure supporting structured credit, mortgage, and asset-backed investments. 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.

Critical Requirement

Direct INTEX implementation experience is required.

Candidates must have hands‑on experience integrating, developing, or supporting INTEX-based analytics solutions. Experience simply using INTEX outputs is not sufficient.

Examples include:

• INTEX API integration
• INTEXCalc
• CDI generation
• Cash flow engine development
• CMO subroutines
• Mortgage or structured finance analytics platforms built on INTEX
• Collateral ingestion and security valuation workflows using INTEX

Core Responsibilities

• Develop and maintain loan‑level mortgage and structured credit analytics.
• Build systems that transform collateral projections into cash flow, valuation, and risk metrics.
• Support prepayment, default, delinquency, recovery, and loss modeling workflows.
• Design and maintain analytical tools used by portfolio managers, traders, and researchers.
• Enhance pricing, surveillance, valuation, and risk infrastructure.
• Deploy and support production quantitative models.

Required Qualifications

• Strong software engineering experience in Java, C++, or another object‑oriented language.
• Hands‑on INTEX implementation experience (required).
• Experience with RMBS, CMBS, ABS, CLO, consumer credit, mortgages, or structured finance.
• Understanding of cash flow modeling, securitization structures, and waterfall mechanics.
• Strong SQL skills and experience working with large‑scale loan‑level and collateral datasets.
• Experience implementing and supporting quantitative models in production.
• Ability to work directly with investment professionals in a fast‑paced environment.

Preferred Qualifications

• Experience with Trepp, Yield Book, BondStudio, CoreLogic, McDash, Black Knight, or LoanPerformance.
• Experience with prepayment, default, recovery, and severity models.
• Experience with cloud platforms, distributed computing, or large‑scale analytics systems.
• Experience building production analytics applications and data services.