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Regulatory & Financial Risk - Consultant - Model Validation

Our Deloitte Regulatory, Risk & Forensic team helps client leaders translate multifaceted risk and an evolving regulatory environment into defensible actions that strengthen, protect, and transform their organizations. Join our team and use advanced data, AI, and emerging technologies with industry insights to help clients bring clarity from complexity and accelerate their path to value creation.

Work you'll do

As a Model Validation Consultant within Regulatory & Financial Risk, you will support model validation work for AI, Generative AI (GenAI), and Agentic AI solutions across client engagements. You will execute validation activities, contribute to documentation and testing, and help teams assess model risk management practices and responsible AI deployment across industries such as Financial Services, Life Sciences, and Technology, Media, and Telecom.

Responsibilities include

• Support end-to-end validation of AI, GenAI, and Agentic AI solutions, from initial review of objectives and data through production readiness and ongoing monitoring.
• Execute fit-for-purpose validation plans, including testing, documentation, and traceability requirements aligned to broader AI risk management processes.
• Assess model design choices, data suitability, assumptions, limitations, and intended use through structured review and testing.
• Evaluate model performance and stability using appropriate methods such as benchmarking, back-testing where applicable, sensitivity testing, stress testing, error analysis, and scenario-based evaluation.
• Support validation of GenAI and Agentic AI behaviors and controls, including response quality evaluation, hallucination and grounding checks for retrieval-augmented generation (RAG), prompt and tool-use testing, guardrails, escalation paths, and audit logging.
• Assess trustworthiness considerations and document observations related to bias and fairness, explainability, robustness, privacy, security, and operational controls.
• Contribute to automated processes for model validation, monitoring, and reporting, including test harnesses, evaluation pipelines, and documentation templates.
• Contribute to project workplans by tracking tasks, identifying risks, and supporting timely delivery of assigned work.
• Prepare clear summaries of validation findings and support development of materials for client stakeholders.
• Collaborate with specialists across Deloitte to strengthen validation approaches and stay current on emerging AI methodologies.

Qualifications

Required:

• Undergraduate degree in Computer Science, Data Science, Artificial Intelligence, Applied Mathematics, or a related field
• 2+ years of experience using Python to develop, test, and maintain code
• 2+ years of experience working with Generative AI frameworks and components such as Hugging Face, OpenAI APIs, Llama models, Gemini, Claude, Granite, retrieval-augmented generation (RAG), or Stable Diffusion
• 1+ years of experience working with Agentic AI frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, or CrewAI
• 2+ years of experience using at least 1 deep learning framework such as PyTorch or TensorFlow/KerasExperience building, testing, or deploying AI solutions on AWS, Azure, or GCP
• Experience with containerization tools such as Docker or Kubernetes
• Understanding of machine learning and deep learning methods, performance assessment, and model validation
• Limited immigration sponsorship may be available
• Ability to travel up to 15%, based on the work you do and the clients and industries/sectors you serve

Preferred:

• Master's degree
• Industry experience in Financial Services, Life Sciences, or Technology, Media, and Telecom
• Experience with JavaScript
• Experience supporting GenAI or Agentic AI solutions in production
• Understanding of AI, GenAI, and Agentic AI risks, bias, mitigation approaches, and responsible use
• Experience with deep learning model training

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

For individuals assigned and/or hired to work in Washington State, Deloitte is required by law to include a reasonable estimate of the compensation range for this role. This compensation range is specific to Washington State and takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $86,700 to $170,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Regulatory & Financial Risk - Consultant - Model Validation

Our Deloitte Regulatory, Risk & Forensic team helps client leaders translate multifaceted risk and an evolving regulatory environment into defensible actions that strengthen, protect, and transform their organizations. Join our team and use advanced data, AI, and emerging technologies with industry insights to help clients bring clarity from complexity and accelerate their path to value creation.

Work you'll do

As a Model Validation Consultant within Regulatory & Financial Risk, you will support model validation work for AI, Generative AI (GenAI), and Agentic AI solutions across client engagements. You will execute validation activities, contribute to documentation and testing, and help teams assess model risk management practices and responsible AI deployment across industries such as Financial Services, Life Sciences, and Technology, Media, and Telecom.

Responsibilities include

• Support end-to-end validation of AI, GenAI, and Agentic AI solutions, from initial review of objectives and data through production readiness and ongoing monitoring.
• Execute fit-for-purpose validation plans, including testing, documentation, and traceability requirements aligned to broader AI risk management processes.
• Assess model design choices, data suitability, assumptions, limitations, and intended use through structured review and testing.
• Evaluate model performance and stability using appropriate methods such as benchmarking, back-testing where applicable, sensitivity testing, stress testing, error analysis, and scenario-based evaluation.
• Support validation of GenAI and Agentic AI behaviors and controls, including response quality evaluation, hallucination and grounding checks for retrieval-augmented generation (RAG), prompt and tool-use testing, guardrails, escalation paths, and audit logging.
• Assess trustworthiness considerations and document observations related to bias and fairness, explainability, robustness, privacy, security, and operational controls.
• Contribute to automated processes for model validation, monitoring, and reporting, including test harnesses, evaluation pipelines, and documentation templates.
• Contribute to project workplans by tracking tasks, identifying risks, and supporting timely delivery of assigned work.
• Prepare clear summaries of validation findings and support development of materials for client stakeholders.
• Collaborate with specialists across Deloitte to strengthen validation approaches and stay current on emerging AI methodologies.

Qualifications

Required:

• Undergraduate degree in Computer Science, Data Science, Artificial Intelligence, Applied Mathematics, or a related field
• 2+ years of experience using Python to develop, test, and maintain code
• 2+ years of experience working with Generative AI frameworks and components such as Hugging Face, OpenAI APIs, Llama models, Gemini, Claude, Granite, retrieval-augmented generation (RAG), or Stable Diffusion
• 1+ years of experience working with Agentic AI frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, or CrewAI
• 2+ years of experience using at least 1 deep learning framework such as PyTorch or TensorFlow/KerasExperience building, testing, or deploying AI solutions on AWS, Azure, or GCP
• Experience with containerization tools such as Docker or Kubernetes
• Understanding of machine learning and deep learning methods, performance assessment, and model validation
• Limited immigration sponsorship may be available
• Ability to travel up to 15%, based on the work you do and the clients and industries/sectors you serve

Preferred:

• Master's degree
• Industry experience in Financial Services, Life Sciences, or Technology, Media, and Telecom
• Experience with JavaScript
• Experience supporting GenAI or Agentic AI solutions in production
• Understanding of AI, GenAI, and Agentic AI risks, bias, mitigation approaches, and responsible use
• Experience with deep learning model training

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

For individuals assigned and/or hired to work in Washington State, Deloitte is required by law to include a reasonable estimate of the compensation range for this role. This compensation range is specific to Washington State and takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $86,700 to $170,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.