Data Scientist, Fraud Detection

Desjardins

. Design models and strategies to quickly detect transactional anomalies .

Posted 10/9/2026full-timeMontréal • CanadaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and deploying fraud detection models and strategies, utilizing advanced analytics and cloud platforms. Proficient in programming languages and data science libraries to optimize fraud detection processes and provide actionable insights.

Highest-signal resume keywords

Fraud Detection StrategiesPython ProgrammingSQL ProgrammingApache Spark (PySpark)Data Visualization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Fraud Detection AnalyticsData AnalysisPredictive ModelingCloud PlatformsData Science Libraries

Soft Skills

Action OrientedInterpersonal SavvyCustomer FocusNimble LearningInnovation

Tools & Technologies

IBM Cloud Pak® for DataMicrosoft AzureRStudioShinyDatabricks

Industry Keywords

Transactional DataFraud Risk ManagementData Visualization DashboardsFraud Mitigation ModelsAd Hoc Analysis

Tech Stack

Tools & technologies

ApacheAzureCloudNumpyPandasPySparkPythonScikit-LearnSparkSQL

About the role

Key responsibilities & impact

Design models and strategies to quickly detect transactional anomalies
Explore, analyze and synthesize information to understand the characteristics of active fraud schemes
Develop strategies for detecting transactional fraud
Test the theoretical performance of fraud mitigation models, rules and tools
Deploy fraud mitigation models, rules and tools into production
Continuously monitor fraud patterns and how well models and strategies are performing
Research and develop predictive variables to improve fraud detection
Develop, update and produce dashboards, data visualizations and various reports
Optimize and automate key fraud detection analytics processes
Provide ad hoc advice on projects to improve fraud risk management tools
Serve as an ad hoc advisor to the risk management teams and business sectors in your field
Monitor the industry to understand and anticipate trends in your field in order to develop and update best practices for the organization.

Requirements

What you’ll need

Bachelor's degree in a related field
A minimum of four years of relevant experience
Please note that other combinations of qualifications and relevant experience may be considered
Experience in analytics with transactional data
Experience working with cloud platforms such as IBM Cloud Pak® for Data or Microsoft Azure
Experience with Apache Spark (via PySpark), Shiny, RStudio and Databricks
Knowledge of French is required
Proficiency in Python or R programming
Proficiency in data science libraries and their limitations, including scikit-learn, pandas, Matplotlib, NumPy and SciPy
Proficiency in SQL programming
Knowledge of GitHub
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