Quantitative Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 16, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Reston, VA
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🧠 - Skills detailed
#Batch #S3 (Amazon Simple Storage Service) #GIT #SciPy #SQL (Structured Query Language) #Spark (Apache Spark) #Python #Business Analysis #Cloud #IAM (Identity and Access Management) #NumPy #Unit Testing #Scripting #Data Lake #Airflow #Shell Scripting #Pandas #Libraries #Computer Science #NoSQL #Datasets #Lambda (AWS Lambda) #EC2 #AWS (Amazon Web Services) #Data Engineering
Role description
• 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).
Skills:
• Business Analysis
• Shell Script
• SQL
• NoSQL
Education:
Bachelor’s degree in Business Administration, Information Systems, Computer Science, or a related field.
• 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).
Skills:
• Business Analysis
• Shell Script
• SQL
• NoSQL
Education:
Bachelor’s degree in Business Administration, Information Systems, Computer Science, or a related field.
