Quantitative Data Scientist: Python Modeling & Risk

Software Technology Inc; Reston (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

Software Technology Inc. in Reston, VA is seeking a Quantitative Data Scientist to build Python-based models for risk analytics and data engineering with AWS and big data tooling.

You'll leverage NumPy, pandas, SciPy, and scikit-learn to design and calibrate models on large mortgage and loan datasets, developing scalable data pipelines and applying advanced risk concepts. This onsite role emphasizes collaboration, rigorous testing, and clear communication of complex results.

Qualifications

• 5+ years in quantitative modeling or data engineering.
• Strong Python and SQL skills for large datasets.
• Experience with Monte Carlo, time-series, and risk modeling.
• Experience with AWS data tooling and data pipelines.

Responsibilities

• Design and maintain quantitative models using Python libraries.
• Work with large mortgage and loan datasets using SQL.
• Calibrate Monte Carlo simulations and time-series models for risk.
• Apply counterparty credit risk concepts like Potential Future Exposure.
• Develop data pipelines on AWS (S3, Lambda, EMR, Glue).
• Follow software engineering practices (Git, CI/CD, tests).

Skills

Python

NumPy

pandas

SciPy

scikit-learn

QuantLib

SQL

Monte Carlo

Time series

Credit risk

AWS

ETL / Data pipelines

Git

CI/CD

Spark

NoSQL

Education

Bachelor's degree

Tools

S3

Lambda

Batch

Glue

EMR

CloudWatch

IAM

EC2

Spark

Hive

Airflow

Git

CI/CD

NoSQL

Job description

Software Technology Inc. in Reston, VA is seeking a Quantitative Data Scientist to build Python-based models for risk analytics and data engineering with AWS and big data tooling.

You'll leverage NumPy, pandas, SciPy, and scikit-learn to design and calibrate models on large mortgage and loan datasets, developing scalable data pipelines and applying advanced risk concepts. This onsite role emphasizes collaboration, rigorous testing, and clear communication of complex results.