AI/ML Risk & Controls Auditor
NY
Contracted
Experienced
What you’ll do in the role:
Conduct Model Audits: Execute a wide range of assurance activities focused on the controls, governance, and risk management of generative AI models used within the organisation.
Model Security & Privacy Reviews: Review and assess privacy controls, data protection measures, and security protocols applied to AI models, including data handling, access management, and compliance with regulatory standards.
Familiarity with GenAI Model: Good understanding of current and upcoming GenAI models.
Adopt New Audit Tools: Stay current with and implement new audit tools and techniques relevant to AI/ML systems, including model interpretability, fairness, and robustness assessment tools.
Risk Communication: Develop clear and concise messages regarding risks and business impact related to AI models, including model bias, drift, and security vulnerabilities.
Data-Driven Analysis: Identify, collect, and analyse data relevant to model performance, privacy, and security, leveraging both structured and unstructured sources.
Control Testing: Test controls over AI model development, deployment, monitoring, and lifecycle management, including data lineage, model versioning, and access controls.
Issue Identification: Identify control gaps and open risks, raise insightful questions to identify root causes and business impact, and draw appropriate conclusions.
What you’ll bring to the role:
Experience: At least 3-4 years’ relevant experience in technology audit, AI/ML, data privacy, or information security.
Auditt Knowledge: Understanding of audit principles, tools, and processes (risk assessments, planning, testing, reporting, and continuous monitoring), with a focus on AI/ML systems.
Communication: Ability to communicate clearly and concisely, adapting messages for technical and non-technical audiences.
Analytical Skills: Ability to identify patterns, anomalies, and risks in model behaviour and data.
•
Education: Master’s or bachelor’s degree (Computer Science, Data Science, Information Security, or related field preferred).
Certifications: CISA, CISSP, or relevant AI/ML certifications (preferred, not required).
Technical Knowledge: Strong understanding of:
AI/ML model development and deployment processes
Model interpretability, fairness, and robustness concepts
•
Privacy frameworks (e.g., GDPR, CCPA)
Security standards (e.g., NIST, ISO 27001/02)
Data governance and protection practices
Rate range - $70-$75
Conduct Model Audits: Execute a wide range of assurance activities focused on the controls, governance, and risk management of generative AI models used within the organisation.
Model Security & Privacy Reviews: Review and assess privacy controls, data protection measures, and security protocols applied to AI models, including data handling, access management, and compliance with regulatory standards.
Familiarity with GenAI Model: Good understanding of current and upcoming GenAI models.
Adopt New Audit Tools: Stay current with and implement new audit tools and techniques relevant to AI/ML systems, including model interpretability, fairness, and robustness assessment tools.
Risk Communication: Develop clear and concise messages regarding risks and business impact related to AI models, including model bias, drift, and security vulnerabilities.
Data-Driven Analysis: Identify, collect, and analyse data relevant to model performance, privacy, and security, leveraging both structured and unstructured sources.
Control Testing: Test controls over AI model development, deployment, monitoring, and lifecycle management, including data lineage, model versioning, and access controls.
Issue Identification: Identify control gaps and open risks, raise insightful questions to identify root causes and business impact, and draw appropriate conclusions.
What you’ll bring to the role:
Experience: At least 3-4 years’ relevant experience in technology audit, AI/ML, data privacy, or information security.
Auditt Knowledge: Understanding of audit principles, tools, and processes (risk assessments, planning, testing, reporting, and continuous monitoring), with a focus on AI/ML systems.
Communication: Ability to communicate clearly and concisely, adapting messages for technical and non-technical audiences.
Analytical Skills: Ability to identify patterns, anomalies, and risks in model behaviour and data.
•
Education: Master’s or bachelor’s degree (Computer Science, Data Science, Information Security, or related field preferred).
Certifications: CISA, CISSP, or relevant AI/ML certifications (preferred, not required).
Technical Knowledge: Strong understanding of:
AI/ML model development and deployment processes
Model interpretability, fairness, and robustness concepts
•
Privacy frameworks (e.g., GDPR, CCPA)
Security standards (e.g., NIST, ISO 27001/02)
Data governance and protection practices
Rate range - $70-$75
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