CGI US is seeking a Quantitative Data Scientist to join their team to support one of their largest customers by developing and maintaining advanced quantitative models for mortgage and loan risk modeling in a fast-paced, agile environment using emerging technologies.
Requirements
- 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.
Responsibilities
- Developing and maintaining advanced quantitative models using Python and SQL
- Optimizing simulations
- Working with large-scale datasets in cloud environments
- Designing and optimizing Monte Carlo simulations and time-series models
- Implementing counterparty credit risk methodologies
- Applying interest rate modeling, derivative pricing, and macro risk factor models
- Utilizing AWS services for data processing and model deployment
Other
- Minimum 5 years of experience in quantitative modeling, data engineering, or a related field (if holding a Bachelor's degree).
- Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
- Hybrid working model is acceptable.
- Role is located at a client site in Reston, VA.
- Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business.
