Quantitative Modeler
We are actively hiring for Quantitative Modeler
Location: Reston, VA (Hybrid)
Quantitative Modeler (Banking, Securities, and Finance)
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Model Development : Develop and validate sophisticated quantitative models for a variety of financial applications, including market risk, credit risk, portfolio optimization, and derivative pricing. This will involve heavy use of Monte Carlo simulations to model complex financial instruments and simulate thousands of possible market scenarios to assess risk and potential returns.
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Time Series Analysis : Build and deploy advanced time series models (e.g., ARIMA, GARCH, and more modern machine learning-based approaches) for forecasting key financial variables like interest rates, volatility, and asset prices.
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Technical Implementation : Utilize Python as the core programming language for model development, backtesting, and automation. Use libraries such as pandas, NumPy, and Scikit-learn, and potentially more specialized finance libraries. Proficiency in SQL is essential for querying and managing large-scale financial datasets from various databases.
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Cloud Computing : Leverage AWS services for model deployment and to manage large-scale computational tasks. This could include using Amazon SageMaker for machine learning workflows, AWS Lambda for event-driven model updates, and Amazon S3 for secure and scalable data storage.
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Collaboration and Communication : Work closely with trading desks, portfolio managers, and risk officers to understand business needs and translate them into robust quantitative solutions. Communicate complex model methodologies and results clearly to both technical and non-technical stakeholders.
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