Model Validation Lead

Guidehouse•Tysons, VA

About The Position

As a Model Validation Lead, you will provide technical and programmatic leadership for the independent validation, governance, and risk management of advanced analytics, machine learning, and AI models deployed in federal environments. You will lead model validation efforts supporting mission-critical use cases across defense and federal financial domains, ensuring models are sound, explainable, compliant, and operationally fit for purpose. You will work closely with data scientists, MLOps engineers, system owners, risk stakeholders, and government counterparts to define validation standards, execute reviews, and ensure alignment with federal, DoD, and financial governance expectations.

Requirements

An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance
Bachelor’s degree in Mathematics, Statistics, Computer Science, Engineering, Economics, or a related quantitative field
FIVE (5) or more years of experience in model validation, model risk management, data science, quantitative analysis, or advanced analytics
Experience validating ML, statistical, and predictive models in regulated or high-risk environments
Experience in Python and analytics tooling used to assess, test, and challenge models
Experience working with large-scale datasets and complex analytical pipelines
Experience leading small teams or workstreams and interfacing directly with senior stakeholders

Nice To Haves

Strong understanding of model risk management concepts, including governance, documentation, and independent review
Experience supporting the Department of Defense, including exposure to Advana or enterprise analytics platforms
Hands-on experience validating models using federal financial, budgetary, accounting, or audit data
Experience validating models deployed on Databricks (e.g., Spark, MLflow)
Ability to translate technical findings into clear, defensible conclusions for government and executive audiences
Exposure to models developed or operationalized in Palantir Foundry
Familiarity with MLOps practices and how validation integrates into CI/CD pipelines
Experience in Azure Government, AWS GovCloud, or other regulated cloud environments
Knowledge of Responsible AI, fairness, bias detection, and explainability techniques
Experience supporting internal or external audits of AI/ML systems
Master’s degree or PhD in a quantitative or technical discipline

Responsibilities

Lead end-to-end model validation activities for ML, AI, and advanced analytical models
Define and oversee validation frameworks covering conceptual soundness, data integrity, methodology, performance, bias, and stability
Review and challenge model assumptions, feature engineering, training approaches, and performance metrics
Assess model robustness, sensitivity, and limitations across operational scenarios
Evaluate model explainability, transparency, and interpretability for technical and non-technical stakeholders
Partner with MLOps and engineering teams to ensure models are production-ready and compliant with governance requirements
Establish validation documentation standards, review artifacts, and approval processes
Support audits, reviews, and governance forums related to AI/ML risk and compliance
Advise clients on model risk management, AI governance, and responsible AI practices
Mentor junior staff and serve as a technical authority within analytics and AI engagements

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Position may be eligible for a discretionary variable incentive bonus
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend