Guidehouse
ModelValidationLead
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“Model Validation Lead at Guidehouse. Skills: Model validation, ML, AI, Python. Lead end‑to‑end model validation activities. Define and oversee validation frameworks”
What You'll Achieve.
Ensure models are sound; Ensure models are explainable; Ensure models are compliant; Ensure models are operationally fit
Industry & Context.
Quantitative analysis; Advanced analytics
Up to 25% travel, Active Secret clearance
What They're Looking For.
Must Have
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 Have
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
What You'll Do.
Lead end‑to‑end model validation activities
Define and oversee validation frameworks
Review and challenge model assumptions
Assess model robustness
Evaluate model explainability
Partner with MLOps and engineering teams
Establish validation documentation standards
and governance forums
Advise clients on model risk management
How You'll Work.
Team & Collaboration
Work closely with data scientists; Work with MLOps engineers; Work with system owners; Work with risk stakeholders; Work with government counterparts; Interfacing directly with senior stakeholders
Communication Scope
Translate technical findings into clear, defensible conclusions
Process & Methodology
Lead small teams, Lead workstreams
Full Job Description
**_Job Family_ :** Data Science Consulting ** _Travel Required_ :** Up to 25% **_Clearance Required_ :** Active Secret **What You Will Do** 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. Key responsibilities include: * Lead end‑to‑end model validation activitie**s** 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 ## **What You Will Need** * An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance. * Bachelor’s degree in
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