AI Systems Analyst

About the Role

As AI systems proliferate across financial services, healthcare, and regulated enterprise environments, the ability to understand, document, and evaluate those systems from a governance and risk perspective becomes critical institutional infrastructure. The AI Systems Analyst sits at the technical core of ELDR Technology's AI practice — conducting AI system assessments, documenting model architectures and data pipelines, and providing the technical grounding that enables ELDR's AI governance advisory work. This is a role for a technically strong analyst who combines ML/AI understanding with governance awareness.

Responsibilities

• Conduct technical assessments of AI and ML systems deployed in client environments — model architecture review, training data provenance analysis, inference pipeline documentation, and monitoring framework evaluation
• Develop technical documentation for AI systems including model cards, system cards, data flow diagrams, and AI governance artefacts
• Support AI risk assessments by providing technical analysis of model behaviour, bias evaluation, and explainability assessments
• Analyse AI/ML pipelines for alignment with regulatory expectations — EU AI Act, NIST AI RMF, OSFI guidelines, and applicable sector requirements
• Maintain ELDR Technology's AI systems knowledge base — tracking model deployment patterns, governance tooling, and regulatory developments
• Contribute technical content to ELDR Intelligence briefs on AI regulatory and technology developments
• Support AI Governance Consultants on client engagements requiring technical depth

Requirements

• 5–10 years of experience in AI/ML engineering, data science, or technical AI governance
• Working knowledge of ML model architectures, training pipelines, and MLOps practices
• Experience with AI governance documentation — model cards, data sheets, algorithmic impact assessments
• Familiarity with AI governance frameworks — NIST AI RMF, EU AI Act risk classification, ISO/IEC 42001
• Proficiency in Python; working knowledge of ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Strong technical writing skills with the ability to translate AI system complexity into governance-relevant documentation
• Undergraduate degree in computer science, mathematics, statistics, or a related field

Preferred Qualifications

• Experience with responsible AI toolkits — IBM AI Fairness 360, Google What-If Tool, Shapley explanations
• Prior work in a regulated environment — financial services AI, clinical AI, or public sector algorithmic systems
• Graduate degree or research background in machine learning, AI ethics, or related fields
• Familiarity with model risk management frameworks — SR 11-7 / OCC 2011-12

What We Offer

• Technical core role within ELDR's growing AI governance practice
• Exposure to AI systems across financial services, healthcare, and government — a uniquely broad vantage point
• Integration with intelligence and advisory functions on cross-disciplinary mandates
• Toronto hybrid with professional development and conference access