Manager decision science

BMO Financial Group; Toronto; On-site; CAD 82,000 - 155,000; Full time

Job summary

Une institution financière basée à Toronto cherche un Senior Analyst, Risk Modeling, pour développer et surveiller des modèles statistiques soutenant les portefeuilles de crédit de détail. Le candidat idéal a au moins 2 ans d'expérience et maîtrise SAS, Python, et SQL. Ce rôle demande de fortes compétences quantitatives et la capacité de communiquer des analyses complexes à des parties prenantes non techniques. Les avantages incluent une assurance santé, un remboursement des frais de scolarité et un plan d'épargne-retraite.

Benefits

Assurance santé

Remboursement des frais de scolarité

Assurance accident

Assurance vie

Plans d'épargne-retraite

Qualifications

• Minimum 2 ans d'expérience en modélisation des risques, analyse de crédit ou analyse quantitative.
• Excellentes compétences en communication, capables de présenter des concepts complexes.
• Expérience avec des ensembles de données importants et des environnements de données complexes.

Responsibilities

• Construire et maintenir des modèles prédictifs pour les portefeuilles de crédit de détail en utilisant des méthodes statistiques et d'apprentissage automatique.
• Analyser des ensembles de données internes pour identifier des tendances et des anomalies.
• Préparer la documentation des modèles et présenter les résultats aux parties prenantes internes.

Skills

Statistiques

Analyse de données

Programmation en SAS

Programmation en Python

Programmation en SQL

Education

Master en STEM (Statistiques, Mathématiques, Économie, etc.)

Job description

Job Details

Date limite pour présenter sa candidature : 02/19/2026

Adresse : 33 Dundas Street West

Groupe de famille d'emploi : Analyses des données et communication de l'information

Senior Analyst, Risk Modeling

The Senior Analyst, Risk Modeling, contributes to the development, enhancement, and monitoring of statistical models supporting retail credit portfolios. This is a technical, data‑driven role requiring strong quantitative skills, experience with complex datasets, and hands‑on programming expertise.

The ideal candidate has a solid grounding in statistics, 2+ years of experience in a financial institution, and strong proficiency in SAS, Python, and SQL. This position is based in Canada and collaborates closely with stakeholders across both Canada and the U.S.

Key Responsibilities

Model Development

• Build, enhance, and maintain predictive models for retail credit portfolios using statistical and machine‑learning methods (e.g., logistic regression, GLM, segmentation).
• Execute the full model development lifecycle: data extraction, feature engineering, model training, variable selection, performance testing, and benchmarking.
• Ensure all work adheres to internal model governance standards, regulatory expectations (e.g., SR 11‑7 principles), and documentation requirements.

Data & Programming

• Manipulate and analyze large datasets sourced from multiple internal systems using SAS, Python, and SQL.
• Perform exploratory data analysis to identify trends, anomalies, and modelling insights.
• Automate processes and build efficient, reusable code components to support ongoing analytics needs.

Documentation & Communication

• Prepare comprehensive model documentation, including methodology, assumptions, variable treatment, limitations, and monitoring results.
• Present findings clearly and concisely to internal stakeholders, including Model Risk, Product, and Strategy teams.
• Support model validation activities by responding to reviewer questions and producing analytical evidence.

Model Monitoring & Maintenance

• Conduct regular model performance monitoring including PSI, KS, AR, calibration, and data‑drift analysis.
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• Identify model degradation and recommend recalibration or redevelopment when required.
• Investigate and resolve data or model‑related issues proactively.

Qualifications

• Master’s degree in a STEM field (Statistics, Mathematics, Economics, Computer Science, Engineering, Data Science, or related discipline).
• Minimum 2 years of experience in risk modeling, credit analytics, or quantitative analysis within a bank or financial institution.
• Strong proficiency with SAS, Python, and SQL for statistical modeling and data processing.
• Strong foundation in probability, statistics, and predictive modeling.
• Demonstrated experience working with large datasets and complex data environments.
• Strong analytical and problem‑solving skills with high attention to detail.
• Excellent communication skills (both written and verbal), with the ability to present complex concepts to non‑technical audiences.

Salary

Salary range: $82,800.00 - $154,800.00 (Canada). Salary may vary based on location, skills, experience, and qualifications. Additional compensation may include commissions or performance bonuses.

Benefits

BMO offers health insurance, tuition reimbursement, accident insurance, life insurance, and retirement savings plans. For more details on our benefits, visit: https://jobs.bmo.com/ca/fr/R%C3%A9mun%C3%A9ration-globale

About Us

BMO is driven by a common purpose: Having the courage to make a difference in lives and business. We innovate, collaborate, and support a strong risk culture. For more information, visit https://jobs.bmo.com/ca/fr.

Recruiter Note

BMO does not accept unsolicited CVs from any source other than the candidate directly. Unsolicited CVs sent to BMO will be considered BMO property. BMO will not pay any placement fees. A recruiting agency must first hold a valid written service agreement before sending CVs.

EEO Statement

American, British, Canadian, French, German, Irish, Italian, Japanese, Korean, Mexican, Nigerian, Polish, Portuguese, Russian, Spanish, Turkish, Chinese, and other diverse candidates are encouraged to apply.