Execute design effectiveness (DE) and operating effectiveness (OE) testing of controls related to Data Governance and AI Governance
Develop and document test steps and test scripts aligned to approved testing methodologies and risk frameworks
Apply professional judgment to determine control effectiveness, identify control gaps, and assess residual risk
Provide risk, control, and process advisory support to business and technology partners related to Data and AI governance
Advise on control design, control enhancements, and process improvements to address identified risks or emerging governance expectations
Benefits
401k Matching
Health Insurance
Dental Insurance
Disability Insurance
Employee Assistance Program
Flexible Hours
Gym Membership
Paid Time Off
Skills
Data Quality Data Management AI Lifecycle Governance Ethical AI Testing Methodologies Risk Frameworks Data Governance Policies Data Governance Standards
Performs validation of models and assesses model risk to confirm model appropriateness and capability for a designated portfolio.
Provides effective challenge during model development and communicates decisions regarding model use to the business to ensure transparency and understanding of models and model risks.
Assesses model's capabilities, stress points and limitations; assesses the associated model risk and the controls in place to mitigate identified risks.
Fosters a culture aligned to BMO purpose, values and strategy and role models BMO values and behaviours in all that they do.
Ensures alignment between values and behaviour that fosters diversity and inclusion.
Benefits
401k Matching
Health Insurance
Paid Time Off
Performance Bonus
Remote Work
Retirement Plan
Skills
Model Validation Risk Assessment Model Development Data Analysis Machine Learning Python SQL
Performs validation of models and assesses model risk to confirm model appropriateness and capability for a designated portfolio.
Provides effective challenge during model development and communicates decisions regarding model use to the business to ensure transparency and understanding of models and model risks.
Assesses model’s capabilities, stress points and limitations; assesses the associated model risk and the controls in place to mitigate identified risks.
Fosters a culture aligned to BMO purpose, values and strategy and role models BMO values and behaviours in all that they do.
Ensures alignment between values and behaviour that fosters diversity and inclusion.
Benefits
401k Matching
Health Insurance
Paid Time Off
Performance Bonus
Remote Work
Retirement Plan
Skills
Finance Model Validation Risk Management API Liquidity Finance Model
Lead enterprise-wide initiatives to continuously identify, assess, and remediate vulnerabilities across AI/ML systems
Oversee the development and execution of vulnerability scanning, penetration testing, and red-teaming exercises specific to AI technologies
Architect and enforce comprehensive AI security governance structures that align with Responsible AI guidelines, regulatory mandates, and organizational risk appetite
Develop policies, standards, and approval processes that ensure full lifecycle oversight of AI/ML systems, supporting auditability, transparency, and accountability in all AI operations
Direct identification, evaluation, and mitigation of risks inherent to AI/ML deployments
Lead risk assessments, threat modeling, and scenario analysis to anticipate potential weaknesses and prioritize mitigation strategies
Spearhead proactive threat intelligence, detection, and response to emerging AI threats
Benefits
401k Matching
Certification Support
Flexible Hours
Health Insurance
Home Office Budget
Learning Budget
Paid Time Off
Remote Work
Skills
AI/ML systems Governance Model Risk Management Data Pipelines cybersecurity architecture advanced defensive capability development runtime environments vulnerability scanning
MSc or PhD in quantitative fields such as statistics, applied mathematics, financial mathematics, data science, actuarial sciences, electrical engineering, or related fields.
Experience in model validation and/or development within a financial institution, particularly in the credit risk area, is a plus.
Certifications: While qualifications like CFA are helpful, they are not mandatory.
Experience in credit risk models, including Stress Testing & loss forecasting, AIRB and Adjudication/Account Management is a plus.
Ability to explain complex technical concepts in everyday language.
Effective communication and stakeholder engagement skills.
Ability to connect the dots between technical issues and business considerations.
Benefits
401k Matching
Health Insurance
Paid Time Off
Performance Bonus
Remote Work
Retirement Plan
Skills
Credit Risk Models Stress Testing Loss Forecasting Model Validation Model Risk Management Quantitative Analysis Statistical modeling
Performs validation of Market Risk and CCR models and assesses model risk to confirm model appropriateness and capability for a designated portfolio.
Provides effective challenge during model development and communicates decisions regarding model use to the business to ensure transparency and understanding of models and model risks.
Assesses model’s capabilities, stress points and limitations; assesses the associated model risk and the controls in place to mitigate identified risks.
Acts as a trusted advisor to Market Risk or CCR model risks.
Influences and negotiates to achieve business objectives.
Benefits
401k Matching
Health Insurance
Paid Time Off
Performance Bonus
Remote Work
Retirement Plan
Skills
Model Risk Model Validation Risk Management Machine Learning Python Data Analysis Market Risk
Execute design effectiveness (DE) and operating effectiveness (OE) testing of controls related to Data Governance and AI Governance
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
Analyze and assess business and governance artifacts, including data governance policies, standards, and procedures, data lineage and data quality documentation, AI governance artifacts
Benefits
401k Matching
Certification Support
Flexible Hours
Health Insurance
Home Office Budget
Learning Budget
Paid Time Off
Remote Work
Skills
Data governance AI Governance Data Quality Data Lineage Data Management AI Lifecycle Governance Ethical AI
Design and implement advanced evaluation methods for LLMs and ML systems
Build and maintain high-quality evaluation datasets, golden sets, challenge sets, and red-teaming corpora
Develop reusable evaluation harnesses and pipelines that support multi-agent workflows, tool use, and retrieval-augmented generation scenarios
Conduct empirical analyses, including statistical tests, error analysis, and ablation studies, to identify model weaknesses and guide model and product improvements
Integrate evaluation metrics and signals into model training loops, deployment gating checks, and continuous monitoring processes
Prototype and validate novel evaluation algorithms inspired by current research in LLM safety, interpretability, and reliability
Produce clear, actionable evaluation reports that translate technical findings into insights for engineering, modeling, product, and business stakeholders
Benefits
401k Matching
Certification Support
Flexible Hours
Gym Membership
Health Insurance
Home Office Budget
Learning Budget
Paid Time Off
Skills
Python Machine Learning Deep Learning LLMs Data Science statistics Data Analysis Programming
Master’s or Ph.D. degree in computer science, finance, mathematics, applied mathematics, statistics, economics, and/or econometrics, physics or engineering
Experience in statistical modeling: logistic regressions, scorecards, survival models
Deep understanding of credit risk concepts (PD, LGD, EAD)
Expert-judgment and override scorecards, modeling philosophy, benchmarking risk rating models and testing of sensitivity to selected risk variables
Assessment of model degradation and data stability using metrics like Population Stability Index (PSI), Kolmogorov-Smirnov (KS) test, and in fairness/bias assessments, including demographic parity and equalized odds
Benefits
401k Matching
Health Insurance
Paid Time Off
Remote Work
Skills
SAS Python Scorecards Statistical modeling Logistic regressions Survival models