Quantitative Data Scientist
- This role is located at a client site in Reston, VA. A hybrid working model is acceptable.
- Strong proficiency in Python, especially with libraries like NumPy, pandas, SciPy, statsmodels, scikit-learn, and QuantLib.
- Advanced SQL skills for handling large and complex mortgage/loan datasets.
- Experience designing and optimizing Monte Carlo simulations and time-series models.
- Solid understanding of counterparty credit risk, including Potential Future Exposure (PFE) methodologies.
- Familiarity with interest rate modeling, derivative pricing, and macro risk factor models.
- Hands-on experience with AWS services such as S3, Lambda, Batch, Glue, EMR, CloudWatch, IAM, and EC2.
- Competence in software engineering practices including Git, unit testing, CI/CD, and shell scripting.
- Experience working with data lakes, NoSQL systems, and tools like Spark, Hive, and Airflow.
- Strong analytical thinking and attention to detail.
- Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.Minimum 5 years of experience in quantitative modeling, data engineering, or a related field (if holding a Bachelor's degree).
- Competitive compensation
- Comprehensive insurance options
- Matching contributions through the 401(k) plan and the share purchase plan
- Paid time off for vacation, holidays, and sick time
- Paid parental leave
- Learning opportunities and tuition assistance
- Wellness and Well-being programs
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