Senior Data Scientist, Credit Risk Strategy

Desjardins

. Design, apply, implement and develop credit risk decision-making strategies .

Posted 11/12/2026full-timeMontréal • CanadaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing predictive models and machine learning algorithms for credit risk management, ensuring alignment with regulatory requirements and industry best practices. Proven ability to mentor team members and simplify complex analytical concepts for diverse audiences.

Highest-signal resume keywords

Predictive Model DevelopmentMachine Learning AlgorithmsCredit Risk ManagementSAS ProgrammingSQL Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModellingRisk Management StrategiesModel ValidationData ScienceStatistical AnalysisFinancial Impact MaximizationMethodological DocumentationGovernance ProcessesAnalytical PracticesQuantification Techniques

Soft Skills

Interpersonal SavvyAction OrientedCustomer FocusNimble LearningInnovation

Tools & Technologies

SASSQLPython

Industry Keywords

Credit RiskGovernanceValidationModel FrameworkAnalytical Concepts

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Design, apply, implement and develop credit risk decision-making strategies
Oversee rigorous methodological documentation meeting governance, validation and model framework requirements
Develop, calibrate and roll out predictive models and advanced machine learning algorithms
Maximize the financial impact of rolled-out strategies and contribute to transforming credit risk management practices
Lead or contribute to large-scale strategic transformation initiatives in data science, predictive modelling and credit risk
Prepare and present methodological files, analyses and recommendations for governance processes, validation exercises, approval committees and risk monitoring bodies
Ensure alignment between business objectives, regulatory requirements, sound risk management and industry best practices
Advise organizational units and simplify complex analytical concepts for non-experts
Mentor, coach and serve as a technical resource for team members
Contribute to the development of the division’s analytical practices

Requirements

What you’ll need

Bachelor’s degree in math, statistics, economics, finance or a related field
A minimum of six years of relevant experience in data science, predictive modelling or credit risk management
Other combinations of qualifications and relevant experience may be considered
Proven experience with the development, validation and implementation of predictive models and machine learning solutions in a production environment
In-depth experience with credit risk management and quantification, and developing risk management decision-making strategies
Experience creating methodology documentation and presenting files intended for governance, model validation and risk management purposes
Knowledge of French is required
Advanced proficiency with SAS, SQL and Python programming tools
Knowledge of machine learning algorithms and their tangible applications in a credit risk environment
Action oriented, Complexity, Customer Focus, Differences, Innovation, Interpersonal Savvy, Nimble learning

Benefits

Comp & perks

Competitive salary and annual bonus
4 weeks of flexible vacation starting in the first year
Defined benefit pension plan that provides predictable, stable income throughout retirement
Group insurance including telemedicine
Reimbursement of health and wellness expenses and telework equipment