Quantitative Developer

🧠 Quantitative Modeler (Python, Statistical Modeling, AWS) Location: Reston VA Hybrid 3 days onsite Job Type: W2 Contract Client: Leading Banking Institution Duration: 6–12 Months (Possible Extension) 🔍 About the Role: We are seeking a highly skilled Quantitative Modeler with a strong background in Applied Mathematics or Statistics to support a premier financial client. This role is ideal for professionals who enjoy working with large datasets, building simulation models, and contributing to cutting-edge financial risk modeling initiatives. 🛠 Key Responsibilities: • Develop and optimize Monte Carlo simulations and time series models. • Manipulate and structure data from relational, NoSQL, and data lake environments. • Combine raw data from various sources to create structured, machine-readable datasets. • Normalize databases and ensure data structure compatibility with application requirements. • Collaborate with engineering and business stakeholders to deliver scalable, production-ready models. ✅ Must-Have Skills: • Strong hands-on experience in Python (NumPy, Pandas, SciPy, statsmodels, scikit-learn, QuantLib) • Proficient in SQL and data manipulation with large mortgage/loan datasets • Experience in Monte Carlo simulations and time series forecasting • Familiarity with AWS (S3, Lambda, Batch, Glue, EMR, CloudWatch, IAM, EC2) • Experience working in production environments with Git, unit testing, and CI/CD pipelines 📈 Preferred Quantitative Knowledge: • Understanding of Potential Future Exposure (PFE) methodologies • Interest rate modeling using statistical/time series techniques • Basic derivative pricing and exposure analytics • Exposure to macro risk factor modeling for mortgage portfolios 🎓 Qualifications: • Master’s degree in Data Science, Computer Science, Applied Mathematics, Financial Engineering (or related field) • Bachelor’s degree with 5+ years of relevant model development experience accepted 💡 Bonus Skills: • Spark, Hive, Airflow • Strong communication skills to work with modelers, analysts, and business teams • Prior experience in the banking/financial services domain