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Data Scientist, Fraud Detection
Desjardins. Design models and strategies to quickly detect transactional anomalies .
Core Competencies
Role fitCore 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 risk management processes.
Highest-signal resume keywords
Fraud Detection StrategiesPython ProgrammingSQL ProgrammingApache Spark (PySpark)Data Visualization
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Fraud Detection AnalyticsData AnalysisPredictive ModelingCloud PlatformsData Science LibrariesR ProgrammingSQLDashboards DevelopmentAutomation of ProcessesTransactional Data Analytics
Tools & Technologies
IBM Cloud Pak® for DataMicrosoft AzureShinyRStudioDatabricksGitHub
Industry Keywords
Fraud Risk ManagementTransactional AnomaliesFraud SchemesFraud MitigationData VisualizationAd Hoc AnalysisBest Practices
Tech Stack
Tools & technologiesApacheAzureCloudNumpyPandasPySparkPythonScikit-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
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