Data & AI Governance Consultant

Review & Update AI Governance Documents

Conduct a structured review of existing AI governance documents, assessing quality, current state, and alignment to governance principles

Lead working sessions with internal teams to gather input, capture gaps, and align required changes

Draft revised governance documents ensuring clarity, consistency, and implementation readiness

Manage review cycles, incorporate feedback, and prepare final sign-off versions Outcome: Updated and implementation-ready versions of all AI governance documents

Identify Gaps & Develop Missing AI Governance Documentation

Benchmark existing documentation against key standards and frameworks (e.g., EU AI Act, ISO 42001, NIST AI RMF)

Conduct structured gap analysis to identify missing governance components, areas of exposure, and priorities for remediation

Develop new governance documents where needed, ensuring alignment with best practices and organizational requirements

Present findings and recommendations to stakeholders clearly and actionably Outcome: Comprehensive gap analysis and creation of missing governance artifacts

Enhance the Data & AI Governance Operating Model

Co-design an improved data management operating model addressing roles, responsibilities, decision rights, processes, and governance structures

Document and iterate the proposed model collaboratively with internal teams

Support validation and approval of the operating model by senior stakeholders Outcome: A refined data & AI governance operating model ready for adoption

Support Implementation of the Responsible AI Program

Assess current maturity, scope, and needs of the Responsible AI program

Participate in and drive structured implementation sprints to operationalize governance processes (e.g., AI risk assessments, AI reviews, lifecycle controls, tooling input)

Conduct enablement workshops to build internal capability and embed Responsible AI practices across teams

Provide ongoing advisory support to stakeholders and leadership on Responsible AI governance and strategic decision-making Outcome: Practical, hands-on support enabling effective rollout of Responsible AI across the organization

Required Skills & Qualifications:

Strong experience in Data Governance, AI Governance, Responsible AI, or related regulatory/compliance roles

Knowledge of ML lifecycles, data pipelines, model evaluation, explainability, bias detection, model monitoring, AI security, robustness, and data quality controls

Deep knowledge and proven experience of working with AI governance frameworks (EU AI Act, ISO 42001, NIST AI RMF, or equivalents)

Demonstrated ability to draft and refine policies, guidelines, and governance documents

Experience facilitating workshops, interviews, and cross-functional working sessions

Ability to design operating models, governance structures, and organizational processes

Excellent communication, analytical, and stakeholder-management skills

Ability to work independently and deliver high-quality outputs within agreed timelines

Experience in driving federated data governance in data mesh and domain-driven environments

Ability to work in a multi-cultural, global environment

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