CGI is seeking a Quantitative Data Scientist to support one of its largest customers in mortgage and loan risk modeling, focusing on developing and maintaining advanced quantitative models to address financial risk and optimize simulations.
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 and working with large-scale datasets in cloud environments.
- Designing and implementing Monte Carlo simulations and time-series models.
- Applying statistical modeling and financial engineering techniques to assess counterparty credit risk.
- Utilizing AWS services such as S3, Lambda, Batch, Glue, EMR, CloudWatch, IAM, and EC2.
- Applying software engineering practices including Git, unit testing, CI/CD, and shell scripting.
- Working with data lakes, NoSQL systems, and tools like Spark, Hive, and Airflow.
Other
- Bachelor’s degree in Business Administration, Information Systems, Computer Science, or a related field.
- 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.
- Willingness to work at a client site in Reston, VA with a hybrid working model acceptable.
- Ability to successfully complete a background investigation.
