Data Scientist at Desjardins, a financial services cooperative, developing advanced analytics, machine learning and AI models. Advising stakeholders and supporting data - driven business decisions.
About the role
- Senior Data Scientist optimizing fraud detection and prevention models for credit applications at Desjardins. Leading complex projects and providing expert advisory support within a hybrid work environment.
Responsibilities
- Develop, enhance and deploy to production advanced application fraud detection and prevention models for credit and financing products.
- Actively contribute to tactical detection activities, including creating, calibrating and optimizing fraud detection rules.
- Analyze and understand complex, emerging and evolving fraud patterns and quickly recommend adjustments or corrective measures suited to the business context.
- Research, design and optimize advanced predictive features related to fraudulent behaviour.
- Recommend and implement strategic and tactical improvements to optimize the effectiveness, robustness and sustainability of detection mechanisms.
- Provide expert advisory support on initiatives to improve fraud risk management tools, controls and practices.
- Serve as a point of reference and influential partner for business sectors and credit risk management, fraud and analytics teams.
- Proactively monitor fraud trends, emerging analytical approaches and market best practices.
Requirements
- Bachelor's degree in machine learning, computer science, statistics, mathematics or a related field
- At least six years of relevant experience in quantitative analysis, modelling or data science
- Extensive experience developing and deploying advanced predictive models
- Experience managing and resolving complex issues with multiple constraints
- Experience working with cloud platforms such as CP4D or Microsoft Azure
- Knowledge of French is required
- Strong ability to simplify complex concepts and communicate clearly with different audiences, both verbally and in writing
- Strong proficiency in developing with Apache Spark (PySpark or Scala) and knowledge of Databricks
- Strong proficiency in deep learning techniques and development frameworks (Keras, TensorFlow, PyTorch, etc.)
- Knowledge of SQL and R, as well as reporting and data visualization techniques
- Expertise in Python programming (scikit-learn, PySpark, pandas, NumPy, SciPy, LangChain, etc.) and in analytics product development practices (Git, MLflow, MLOps concepts)
Benefits
- 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
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