Open Systems Technologies
Quantitative Model Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Quantitative Model Developer with a contract length of "unknown," offering a pay rate of "unknown." Requires a Master’s in Data Science or related field, 5+ years of experience, proficiency in Python and SQL, and AWS expertise.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
October 15, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Reston, VA
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🧠 - Skills detailed
#Pandas #Time Series #S3 (Amazon Simple Storage Service) #Data Science #AWS Glue #IAM (Identity and Access Management) #Datasets #SQL (Structured Query Language) #AWS Lambda #AWS EMR (Amazon Elastic MapReduce) #Unit Testing #GIT #Batch #EC2 #AWS (Amazon Web Services) #SciPy #Cloud #NumPy #Computer Science #Lambda (AWS Lambda) #Python
Role description
Education/Experience
Master’s in Data Science, Computer Science, Applied Math, or Financial Engineering; or Bachelor’s in same fields with 5+ years of quantitative model development experience in Python, SQL.
Technical Skills
Proficiency in Python with strong experience using quantitative/statistical packages (NumPy, pandas, SciPy, statsmodels, scikit-learn, QuantLib).
Strong SQL skills for working with large mortgage/loan datasets.
Ability to design, implement, and optimize Monte Carlo simulations and time-series models.
Experience building, testing, and maintaining production-ready Python/Shell code with Git, unit testing, and CI/CD.
Hands on experience with AWS services like Amazon S3, AWS Lambda, AWS Batch, AWS Glue, AWS EMR, Cloudwatch and IAM , EC2
Quantitative Modeling Knowledge
Familiarity with Potential Future Exposure (PFE) methodologies for counterparty credit risk.
Understanding of interest rate modeling using time series techniques.
Basic understanding of derivative pricing and exposure dynamics.
Exposure to macro risk factor models relevant to mortgage portfolios.
Soft Skills
Strong analytical and problem-solving skills with attention to detail.
Ability to clearly communicate results and technical design to both modelers and business stakeholders.
Education/Experience
Master’s in Data Science, Computer Science, Applied Math, or Financial Engineering; or Bachelor’s in same fields with 5+ years of quantitative model development experience in Python, SQL.
Technical Skills
Proficiency in Python with strong experience using quantitative/statistical packages (NumPy, pandas, SciPy, statsmodels, scikit-learn, QuantLib).
Strong SQL skills for working with large mortgage/loan datasets.
Ability to design, implement, and optimize Monte Carlo simulations and time-series models.
Experience building, testing, and maintaining production-ready Python/Shell code with Git, unit testing, and CI/CD.
Hands on experience with AWS services like Amazon S3, AWS Lambda, AWS Batch, AWS Glue, AWS EMR, Cloudwatch and IAM , EC2
Quantitative Modeling Knowledge
Familiarity with Potential Future Exposure (PFE) methodologies for counterparty credit risk.
Understanding of interest rate modeling using time series techniques.
Basic understanding of derivative pricing and exposure dynamics.
Exposure to macro risk factor models relevant to mortgage portfolios.
Soft Skills
Strong analytical and problem-solving skills with attention to detail.
Ability to clearly communicate results and technical design to both modelers and business stakeholders.
