Overview
On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)
Able to Provide Sponsorship
Skills
Analytics
Apache Spark
Artificial Intelligence
Banking
Basel
Computational Finance
Computer Science
Credit Risk
Finance
Internal Auditing
Kubernetes
Machine Learning (ML)
Mathematics
Modeling
Natural Language Processing
NumPy
Pandas
PyTorch
Python
Quartz
Regulatory Compliance
Scala
Statistics
TensorFlow
Terraform
Text Mining
scikit-learn
Senior Quantitative Developer Machine Learning & Regulatory Credit Risk
Quantitative Developer
Machine Learning & Regulatory Credit Risk
Job Details
Westerville, OH (Hybrid 3 days onsite)
- 10+ years in quantitative development or model risk analytics, preferably in banking, regulatory modeling, or enterprise risk domains.
- Advanced expertise in:
- Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow)
- Apache Spark (Scala) for distributed ML workloads
- Azure Kubernetes Services (AKS), Terraform, MLflow
- Deep understanding of U.S. regulatory frameworks: Basel III/IV, CECL, SR 11-7, SR 15 18/19, and CCAR.
- Proven experience building interpretable ML models and documenting them for use in audited and regulated environments.
- Strong communication skills for cross-functional collaboration with MRG, internal audit, compliance, and technology teams.
- Degree in a quantitative discipline such as Mathematics, Computer Science, Financial Engineering, or Statistics (PhD or Master s preferred).
- Prior work with regulatory capital model development or validation teams.
- Familiarity with risk modeling architecture, tools, or data pipelines (Athena, Quartz).
- Experience implementing AI/ML model fairness, bias detection, and transparency controls in regulated environments.
- Participation in regulatory exams (OCC, Federal Reserve, FDIC) or model submission cycles.
- Background in text mining, survival modeling, or NLP for financial documents is a plus.
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