Specialist II - Control Tester – Data & AI Governance

BMO•Chicago, IL

14d

About The Position

The Control Tester – Data & AI Governance is responsible for executing and leading control testing activities related to Data Governance and AI Governance. This role focuses on assessing design effectiveness and operating effectiveness of controls, understanding end‑to‑end processes through walkthroughs, analyzing governance artifacts, and identifying, documenting, and communicating control issues. The role requires strong testing judgment, the ability to develop and execute test steps, and effective communication with business partners, risk partners, and control owners.

Requirements

3–5 years of relevant experience in control testing, risk management, audit, or governance functions.
Demonstrated experience performing control design and operating effectiveness testing.
Ability to understand and document business and technology processes through walkthroughs.
Strong analytical skills with the ability to interpret complex governance and technical artifacts.
Strong written and verbal communication skills, including issue writeups and stakeholder discussions.

Nice To Haves

Experience in Data Governance, AI Governance, Model Risk Management, or Technology Risk.
Familiarity with data management concepts, AI/ML model lifecycles, and governance frameworks.
Experience engaging directly with business and risk partners in a testing or oversight capacity.

Responsibilities

Execute design effectiveness (DE) and operating effectiveness (OE) testing of controls related to Data Governance and AI Governance, including data quality, data management, AI lifecycle governance, and ethical AI controls.
Develop and document test steps and test scripts aligned to approved testing methodologies and risk frameworks.
Perform reperformance testing, sampling, and evidence validation to assess control execution
Apply professional judgment to determine control effectiveness and identify control gaps.
Lead and conduct walkthroughs with control owners and stakeholders to understand end‑to-end processes related to in-scope control activities
Document process overviews, analyze control descriptions and key risks based on walkthroughs and artifact review.
Maintain a working understanding of how data and AI controls operate within business and technology processes.
Analyze and assess business and governance artifacts, including: Data governance policies, standards, and procedures Data lineage and data quality documentation AI governance artifacts (e.g., model governance documentation, lifecycle controls, approval evidence) Evaluate whether artifacts sufficiently demonstrate control design and operation.
Identify, document, and clearly articulate control deficiencies, design gaps, and operating issues, including root cause analysis.
Draft clear, risk‑based issue descriptions and support issue validation discussions with business and risk partners.
Communicate testing results, issues, and recommendations to stakeholders in a clear and professional manner.
Act as a primary testing contact for business partners, technology teams, and risk partners for assigned controls.
Support ongoing dialogue to clarify control intent, evidence expectations, and remediation actions.
Contribute to continuous improvement of Data & AI governance testing practices.
Create and maintain high‑quality testing documentation, including workpapers, test scripts, walkthrough notes, and testing conclusions.
Ensure testing work meets quality standards, methodology requirements, and service level expectations.