Job Title: Senior Quantitative Developer – ML & Regulatory Credit Risk Location: Westerville, OH (Hybrid – 3 days onsite) Type: Contract Overview: We are seeking a highly experienced Senior Quantitative Developer to support regulatory credit risk model development and deployment. This role is ideal for professionals with a strong background in machine learning, cloud technologies, and regulatory risk frameworks, looking to make a significant impact within a global financial institution. Key Responsibilities: • Design and implement scalable regulatory credit risk models including PD, LGD, and EAD using Python and Apache Spark (Scala). • Deploy machine learning solutions to Azure Kubernetes Service (AKS). • Develop ML pipelines leveraging MLflow, Terraform, and Azure DevOps. • Apply Explainable AI (XAI) techniques such as SHAP, LIME, and counterfactual analysis. • Oversee full lifecycle management of CECL and CCAR models. • Ensure compliance with Basel III/IV, SR 11-7, OCC, and Federal Reserve regulatory standards. • Integrate alternative data sources (e.g., NLP, ESG, unstructured text) into modeling pipelines. • Collaborate with cross-functional teams, including risk management, model validation, and data engineering. Qualifications: Minimum 10 years of experience in quantitative development, risk modeling, or enterprise risk analytics. Expert-level proficiency in: • Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow) • Apache Spark (Scala), MLflow, Terraform, Azure DevOps • Regulatory risk frameworks including Basel, CECL, CCAR, SR 11-7 Strong academic credentials: Master’s or PhD in Mathematics, Statistics, Financial Engineering, or related field. Exceptional communication skills with the ability to interact with regulators and internal stakeholders effectively.