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Quantitative Engineer
1 month ago
The Quantitative Engineer will be responsible for conducting theoretical and empirical research using public and proprietary data in various areas of mortgage finance. This role involves applying advanced mathematical, statistical, and econometric techniques to provide innovative solutions that support business strategies and initiatives. Responsibilities: Develop, implement, and test all components using Python/R for financial models, algorithms, cash flow simulations, and pricing/risk metrics calculations in end-user or production computing systems for use in business decisions, financial and regulatory reporting, and risk management. Use advanced analytics and data science techniques to efficiently translate complex mathematical, business, and financial modeling logic into software code. Design and execute test cases for modeling and analytical software applications to ensure they meet business needs and model requirements. Design and execute modeling application systems via distributed computing both on-premise and on an external cloud. Execute model application runs, process/validate model outputs, and produce/review quantitative reports for business use. Communicate complex quantitative analysis in a clear, precise, and actionable manner both verbally and in writing. Qualifications: PhD preferred; MS in Computer Science, Statistics, Math, Engineering, or related field required. 1+ years of experience specifically with deep learning (e.g., CNN, RNN, LSTM). Demonstrated skills with Jupyter Notebook, AWS SageMaker, Domino Datalab, or comparable environments. Experience with econometric modeling and statistical analysis. Experience with the implementation and creation of various models and algorithms, including regression and statistical models. Knowledge of AI or machine learning techniques is desirable. Strong programming experience in Python/R. Familiarity with AWS/Cloud environment. Proficiency in Linux/UNIX environments. Knowledge of mortgage mathematics is highly desirable. Experience working with financial data, analytics, and cash flow applications. Understanding of the Credit Risk Model, Conservator Capital Framework (CCF), and Credit Risk Transfer is a plus. Understanding of agency prepayment models, MBS data, and the MBS market. This is a remote position requiring the ability to work effectively in a home office environment with moderate noise levels. #J-18808-Ljbffr