Senior Data Scientist Model Validation Role

AI AI LLC

United States

24 days ago

Role details

Contract type

Permanent contract

Employment type

Part-time (≤ 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

arc.dev

Tech stack

Artificial Intelligence Python (Programming Language) Machine Learning SQL Databases Feature Engineering Model Validation Information Technology Data Lineage Production Code

Job description

Conduct independent validation of credit risk models used across the customer lifecycle including behavioural risk models and AI/ML-based credit decisioning models
Assess conceptual soundness, model methodology, assumptions, variable selection, feature engineering techniques, and model design.
Help establish and maintain a model inventory covering all models in production, development, and retirement stages, including risk tier and metadata
management.
Define and implement model materiality classification criteria (High / Medium / Low) to prioritize validation activities and resource allocation.
Support development of MRM policies, procedures, and standards alignedwith SR 26-2 (the current interagency guidance issued April 2026, superseding
SR 11-7) from inception, applying its principles-based, risk-proportionateapproach.
Execute validation using champion-challenger framework, benchmarking, stresstesting, and sensitivity analysis.
Validate model implementation by verifying that production code and system outputs match approved model specifications.
Assess data quality, data lineage, and feature appropriateness, including review of credit bureau data usage.
Define ongoing monitoring standards including PSI, CSI, Gini/KS tracking thresholds, and escalation triggers for model performance degradation. Review
periodic model performance monitoring reports
Evaluate fairness, bias, and model transparency considerations particularly forAI/ML models used in credit decisioning under ECOA/Reg B.
Author end-to-end validation reports covering scope, data assessment,methodology review, findings, risk ratings, compensating controls, and formal
recommendations (Approve / Conditionally Approve / Reject).
Assign and justify model risk ratings based on model materiality, complexity, intended use, and potential business impact.
Review model development documentation, implementation documents,monitoring reports, and change management records.
Ensure all MRM activities comply with SR 26-2, OCC Bulletin 2026-13,ECOA/Reg B, and FCRA regulatory requirements. Apply SR 26-2’s risk-based,
proportionate approach to validation prioritization and governance design.
Partner with model development, risk, compliance, and technology teams to discuss findings and agree on remediation plans and model change
management processes.
Present validation results to senior management, model governance committees, and client stakeholders.
Support external audits, regulatory examinations, and client due diligence activities.

Requirements

5-7 years of experience in Model Validation and Quantitative Risk Management
Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science,
Engineering, or a related quantitative field required. Master’s degree or PhD.
Prior experience working within a formal MRM function is required.
Prior experience supporting U.S. banks, credit unions, fintechs, or consumer lenders.
Strong proficiency in Python, SQL, SHAP and LIME for model explainability,familiarity with champion-challenger frameworks and model monitoring tooling.
Experience with statistical model validation techniques, Machine learning model
assessment and Credit bureau data
Proven ability to work with global stakeholders across time zones
Proven ability to produce clear, structured, audit-ready validation reports suitable for regulatory examination and model governance review