Software Engineering Professional (Java, Springboot)

Freddie Mac•McLean, VA

1d•$109,000 - $163,000•Onsite

About The Position

Freddie Mac's mission is to make home possible, and this role contributes to that by being part of a technology team focused on exciting challenges. The Financial Engineering team is where models are converted into software, producing numbers that drive business decisions for automated loan underwriting and distressed loan decisions. This Software Engineering Professional position is within the Model Applications Development team, focusing on creating microservices, Kubernetes, and High Availability Applications, while ensuring operational excellence.

Requirements

Minimum of 2-4 years relevant professional experience
Master's degree in Computer Science, Computational Finance or a directly related quantitative field.
Back End Skills: Java - REST/Json API, Spring Boot, Hibernate, Database (SQL/NOSQL)
Front End Skills: Web based application skills (Angular, JavaScript, TypeScript)
Automation Testing: Junit, Automated Performance and Regression/Functional Testing
Devops Tools: git, gradle, Docker, Jenkins, Kubernetes, OCP/AWS, CI/CD pipeline.

Nice To Haves

Experience with Apache camel, Active MQ, Apigee, ONNX is preferred
Experience in mortgage origination and underwriting applications is preferred.
Familiarity with either Python or SAS are preferred.
Experience in handling borrower Credit Bureau reports (Equifax, Experian and TransUnion) preferred.
Experience with Modeling and Simulations is preferred.

Responsibilities

Developing model applications and microservices using Java or Python web services frameworks.
Maintaining underwriting models and credit data processing.
Building dashboards and customer support UI.
Performance tuning and stress testing services.
Participating in model tie outs, identifying and resolving issues in reconciling with model results.
Fixing software security vulnerabilities identified in SAST and FOSS scanning.
Automating and deploying Financial Models developed using ML algorithms.
Deploying model configuration with market and economic data for loss mitigation models.
Providing APIs to Financial Models to integrate with IT applications.
Performance tuning and stress testing Models.
Participating in model tie outs. Identifying and resolving any issues in reconciling with model results.
Fixing software security vulnerabilities identified in SAST and FOSS scanning.