Lead - AI Governance & QA Auditor - Data Scientist, AI Systems Audit

Position - Lead - AI Governance & QA Auditor - Data Scientist, AI Systems Audit, Compliance, AI Governance, AI Explainability, Python

Job Summary

We are seeking a highly skilled AI Governance, and QA Auditor to evaluate, audit, and ensure the responsible, ethical, and compliant use of Artificial Intelligence and Machine Learning systems. This role is central to maintaining trust, fairness, transparency, and regulatory alignment across AI/ML initiatives, while driving continuous improvement in model development, deployment, and monitoring practices. The candidate will collaborate with data scientists, engineers, risk/compliance teams, and business stakeholders to establish and enforce AI governance frameworks, leveraging advanced tools such as IBM Watsonx Governance.

Key Responsibilities

AI Assurance & Quality Auditing

• Design framework for technical auditing of AI/ML systems that avoid costly mistakes.
• Conduct independent audits of a variety of AI/ML systems in the areas of Gen AI, Deep Learning, Machine Learning, Natural Language Processing and Computer Vision.
• Verify compliance with benchmark standards, external regulations, and ethical AI principles.
• Assess data quality, feature engineering practices, and model development pipelines for reproducibility, fairness, and bias mitigation.
• Evaluate ML model performance, robustness, explainability, and alignment with intended business outcomes.
• Review deployment processes, model versioning, and monitoring practices to ensure traceability and accountability.
• Utilize Watsonx Governance and other enterprise AI governance tools to audit and validate responsible AI practices.

AI Governance & Risk Management

• Define, implement, and maintain AI governance frameworks, policies, and best practices.
• Identify AI risks (bias, drift, adversarial attacks, misuse) and recommend mitigation strategies.
• Ensure compliance with AI regulations and standards (e.g., EU AI Act, NIST AI RMF, ISO 42001, GDPR, industry-specific frameworks).
• Establish governance checkpoints across the AI lifecycle (data collection, training, validation, deployment, monitoring).
• Leverage Watsonx Governance for automated policy enforcement, lineage tracking, and audit readiness.

Compliance & Ethical AI

• Audit AI/ML systems for fairness, inclusivity, accountability, and transparency.
• Ensure model documentation, datasheets, and audit trails are consistently maintained.
• Provide assurance reports for regulators, clients, and internal executives.
• Monitor emerging AI regulations and update governance policies accordingly.

Collaboration & Advisory

• Partner with Data Science, MLOps, and Product teams to embed assurance-by-design practices.
• Educate stakeholders on AI risks, governance policies, and responsible AI principles.
• Act as an internal advisor for audits, compliance reviews, and external certifications.

Qualifications & Skills:

Education

Bachelors degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field.

Masters/PhD or certification in AI Governance, Risk & Compliance, or Data Ethics is preferred.

Required Experience

• 10+ years of overall professional experience, with at least 5 years in AI/ML model development, assurance, risk management, or audit functions.
• Hands-on expertise with Data Science workflows, ML model evaluation, and MLOps pipelines.
• Prior experience in regulatory compliance, IT audit, or QA within financial services, healthcare, or other regulated industries is a plus.
• Technical Skills
• Strong understanding of machine learning, deep learning, and generative AI.
• Familiarity with AI auditing tools (e.g., Fairlearn, Aequitas, SHAP, LIME, Explainable AI frameworks).
• Proficiency in Python, SQL, and model evaluation libraries.
• Knowledge of cloud platforms (AWS, Azure, GCP) and enterprise governance solutions such as IBM Watsonx Governance, Vertex AI Model Monitoring, and Watson OpenScale.
• Governance & Regulatory Skills
• Knowledge of AI risk management frameworks (NIST AI RMF, ISO 42001, OECD AI Principles).
• Understanding of data protection and privacy laws (GDPR, HIPAA, CCPA).
• Ability to translate technical findings into executive-level risk and compliance reports.

Soft Skills

• Strong analytical and critical thinking with attention to detail.
• Excellent communication and stakeholder management skills.
• Ability to act as an independent, objective voice in AI governance matters.