Quantitative Data Scientist

• 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).

Education:
Bachelor's degree in Business Administration, Information Systems, Computer Science, or a related field.

Skills:

• Business Analysis
• Shell Script
• SQL
• NoSQL