Model Risk Quant Developer -New York, NY -Hybrid

FinTrust Connect; New York (NY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

A financial services company is seeking a Model Risk Quant Developer in New York, NY. The successful candidate will have 5 to 10 years of quantitative development experience, expertise in Python, and familiarity with model validation processes. Responsibilities include building robust analytics utilities and optimizing compute paths for risk models. This is a hybrid position offering the opportunity to work closely with validation teams to ensure comprehensive model testing and compliance with SR 11 7 standards.

Qualifications

• 5 to 10 years in quantitative development in banking or buy side.
• Expert in Python with strong SQL skills.
• Experience in model validation and testing.

Responsibilities

• Implement robust pricing and risk analytics and backtesting utilities.
• Optimize compute paths and serialize results for explainability.
• Build harnesses for challenger and benchmark models.

Skills

Python

SQL

C++ or Java

Familiarity with SR 11 7 controls

NumPy

Pandas

SciPy

scikit-learn

PyTorch or TensorFlow

Data engineering awareness

Tools

CI/CD

Job description

About the job Model Risk Quant Developer -New York, NY -Hybrid

FinTrust Connect -New York, NY -Hybrid

Share Your Resume and Build Your Future!

Join our Talent Community for New York. Demand is strong for Python first quant developers who partner with model risk and validation teams to productionize libraries, automate back tests, and support SR 11 7 driven testing and controls.

As a Model Risk Quant Developer you will build and harden production grade code that enables risk models and validation tools across market credit and liquidity domains. You will collaborate with quants and validators and technology to deliver reproducible results, traceable data, and exam ready evidence.

Requirements

• 5 to 10 years in quantitative development in banking or buy side
• Expert Python with strong SQL and exposure to C++ or Java nice to have
• Experience supporting model validation and testing and benchmarking
• Familiarity with SR 11 7 controls and model lifecycle and documentation expectations
• Libraries and tools NumPy and Pandas and SciPy and scikit learn and PyTorch or TensorFlow as needed
• CI and CD unit tests and regression suites and artifact versioning and containerization
• Data engineering awareness for clean inputs and lineage

Responsibilities

• Implement robust pricing and risk analytics and backtesting utilities that validators can run repeatably
• Optimize compute paths and serialize results for explainability and audit
• Build harnesses for challenger and benchmark models and sensitivity and stability checks