remote
Model Risk Management Lead, Machine Learning - Affirm
ML Engineer
Lead the model risk management function for advanced machine learning models, ensuring robust risk assessment, compliance, and governance across the organization while driving continuous improvement and stakeholder collaboration.
About the role
Key Responsibilities
- Lead the end‑to‑end model risk management lifecycle for machine learning models, from development through deployment and monitoring.
- Design and enforce model validation, documentation, and audit frameworks that meet regulatory and internal standards.
- Collaborate with data science, engineering, and product teams to embed risk controls into model development pipelines.
- Conduct regular model performance reviews, bias assessments, and impact analyses to detect and mitigate risks.
- Prepare and present risk findings to senior leadership, audit committees, and external regulators.
Requirements
- 10+ years of experience in model risk, quantitative risk, or related fields, with a focus on machine learning.
- Deep knowledge of model validation techniques, statistical testing, and regulatory frameworks (e.g., Basel, FFIEC).
- Proficiency in Python and data‑analysis libraries (pandas, scikit‑learn) for model evaluation.
- Strong communication skills and ability to translate complex risk concepts to non‑technical stakeholders.
- Experience with cloud platforms (AWS, Azure) and model deployment pipelines is a plus.
Skills
machine learningpython