Data Scientist validating quantitative P&C insurance models for Desjardins Group. Applying statistics, machine learning, and regulatory expertise to model risk.
Responsibilities
Ensure modelling processes appropriately use available data based on characterization, quality, and processing
Validate predictive modelling against required standards and Desjardins Group quality criteria
Analyze business needs and confirm model suitability through validation
Ensure programming for data preparation, mining, model development, evaluation, support, rollout, and management meets standards
Use advanced statistical, machine learning, and artificial intelligence methods to test methodologies
Help draft guidelines and methods and shape methodological and technological choices
Advise and train teams on quantitative model validation methods
Identify opportunities to optimize rules and systems and develop data management and modelling support tools
Represent teams with internal stakeholders
Monitor industry trends and update model validation practices
Ensure alignment with regulatory expectations for P&C insurance
Requirements
Bachelor’s degree in a related field (actuarial science, statistics, applied mathematics, engineering, data science, computer science)
Minimum of six years of relevant experience, including a minimum of three years in analytics or modelling
Experience in P&C insurance (pricing, reserving, claims, capital/catastrophes, analytical marketing)
Other combinations of qualifications and relevant experience may be considered
Knowledge of French is required
Intermediate knowledge of English
Knowledge of mathematical modelling and statistics
Proficiency in Python, R, SQL, and SAS
Proficiency with risk management models in at least one specified P&C insurance area
Knowledge of property and casualty insurance
Knowledge of Canadian regulatory frameworks, including model risk management expectations, IFRS 17, MCT, and AMF/OSFI guidelines
Benefits
Competitive salary and annual bonus
4 weeks of flexible vacation starting in the first year
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