Data Scientist

• Mine big data to discover actionable fraud insights
• Develop and deploy product- and channel-specific fraud strategies
• Reduce fraud risk while balancing loss, customer experience, and operational capacity
• Identify new fraud vectors and optimize existing rules using SQL, Python, and fraud authentication solutions
• Conduct intra-day and weekly monitoring across products, channels, and risk segments
• Provide ad-hoc analysis to support executive-level decision-making
• Continually optimize, improve, and strengthen fraud strategy and analytics capabilities
• Independently investigate new, high-risk fraud threats under tight timelines
• Learn and manage first- and third-party fraud

Data Scientist II

• Oversee data mining, evaluation, feature engineering, quality inspection and adjustment of available data, and selection of predictors for complex predictive modeling mandates
• Analyze client and partner business needs, generate hypotheses and lead mandates through operationalization and rollout
• Apply advanced statistical, machine learning and artificial intelligence methods to develop and optimize models and segmentations
• Create programming to prepare and mine data, and develop, evaluate, support, roll out and manage complex models
• Prepare presentations and data visualizations to support business decisions and management consideration
• Draft guidelines and data modelling methods, support documentation, and prepare and deliver training
• Identify opportunities to improve rules and systems, anticipate impacts of changes and enhance data management tools
• Advise stakeholders and decision-making bodies on data use, and act as a subject matter expert and coach
• Interact with stakeholders across fields to understand issues, communicate findings and influence decision-making

Data Scientist, Data Valorization

• Provide data needed to make business decisions, develop solutions and services adapted to business issues, and understand member and client behaviour
• Lead internal and external stakeholders in model development projects and complex strategic interventions in advanced analytics and artificial intelligence
• Mine multiple data sources to solve highly operationally and conceptually complex business problems
• Serve as an expert advisor and subject matter expert on data use for stakeholders, and as a resource person and coach for decision-making bodies
• Oversee data mining, evaluation, feature engineering, quality inspection and adjustment of available data, and predictor selection for complex predictive modeling mandates
• Analyze client and partner business needs, generate hypotheses, lead mandates, coordinate operationalization and rollout
• Apply advanced statistical, machine learning and artificial intelligence methods; develop and optimize models and segmentations
• Create programming to prepare and mine data; develop, evaluate, support, roll out and manage highly complex models
• Prepare presentations and data visualizations to support business decisions and present them to management
• Draft guidelines and data modelling methods, support documentation, and prepare and deliver training
• Identify opportunities to improve rules and systems, anticipate impacts of changes, and enhance data management tools
• Interact with stakeholders across a wide range of fields to understand and communicate issues and influence decision-making

• Ensure modelling processes make appropriate use of available data based on characterization, quality and processing as part of strategic initiatives
• Use the validation process to ensure predictive modelling is carried out according to established standards and meets Desjardins Group’s quality criteria
• Analyze business needs behind models and confirm model suitability through validation
• Ensure programming for preparing and mining data and for developing, evaluating, supporting, rolling out and managing innovative and conceptually complex models meets required standards
• Use advanced and innovative statistical, machine learning and AI methods to test methodologies proposed by the first line of defence
• Validate risk and financial valuation models, predictive models, machine learning models, natural language processing models, speech recognition models and generative AI solutions
• Assess model robustness, performance, stability, explainability and related risks, including algorithmic bias, model drift and responsible AI issues
• Help draft governance documents, methods, and methodological and technological approaches
• Advise and train teams on quantitative model validation methods and help advance these methods to accelerate delivery
• Represent the teams in dealings with internal stakeholders
• Monitor the industry to understand and anticipate emerging trends

Data Scientist, Financial and AI Models

• Own the analytical function end-to-end for an embedded business unit in growth, product, AI and automation, or strategic partnerships
• Define the business problems and decisions that analyses should address
• Define metrics and build reports
• Run analyses and design experiments
• Surface data insights that improve key business metrics
• Present recommendations to product, growth, finance, or operations counterparts
• Explain what is happening, why it is happening, and recommended next steps
• Drive initiatives through execution and outcomes
• Collaborate with business-unit stakeholders and the central Data Science & Analytics team

Senior Data Scientist

• Join the central Data Science & Analytics team and embed within growth, product, AI and automation, or strategic partnerships
• Own the analytical function for an assigned business unit end-to-end
• Define business problems, clarify the decision each analysis will inform, and challenge flawed questions
• Define metrics and build reports
• Run analyses and design experiments
• Surface insights that improve key business metrics
• Present recommendations to product, growth, finance, or operations counterparts
• Explain what is happening, why it is happening, and recommended next steps
• Drive decisions and execute initiatives through completion

Associate Data Scientist

• Join the central Data Science & Analytics team while embedding in a core business area: growth, product, AI and automation, or strategic partnerships
• Own the analytical function for the assigned business unit end-to-end
• Define business problems, analytical questions, and decisions to inform
• Define metrics, build reports, run analyses, design experiments, and surface insights
• Bring recommendations to product, growth, finance, or operations counterparts
• Explain what is happening, why it is happening, and recommended next steps
• Drive decisions and see initiatives through to execution
• Help Jerry.ai scale from 5M to 50M customers and become a $10B business

• Embed within a core business area: growth marketing, product development, AI and automation, or strategic partnerships
• Own the analytical function for the assigned business unit end-to-end
• Define business questions and the decisions they should inform
• Challenge flawed questions before analysis begins
• Define metrics and build reports
• Pull, structure, and interpret data
• Run analyses and design experiments
• Surface insights that improve key team metrics
• Present recommendations to product, growth, finance, or operations counterparts
• Explain what is happening, why it is happening, and recommended next steps
• Drive decisions and follow execution through to outcomes

• Join the central Data Science & Analytics team while embedding in growth, product, AI and automation, or strategic partnerships
• Own the analytical function for an assigned business unit end-to-end
• Define business problems, clarify the decisions they inform, and challenge flawed questions
• Define metrics and build reports
• Run analyses and design experiments
• Surface insights that improve key business metrics
• Present recommendations to product, growth, finance, or operations counterparts
• Explain what is happening, why it is happening, and recommended next steps
• Drive analytical work through execution and measurable outcomes

Staff Data Scientist

• Ensure modelling processes make appropriate use of available data based on characterization, quality and processing as part of strategic initiatives
• Use the validation process to ensure predictive modelling is carried out according to established standards and meets Desjardins Group’s quality criteria
• Analyze business needs behind models and confirm model suitability through validation
• Ensure programming for preparing and mining data and developing, evaluating, supporting, rolling out and managing complex models meets required standards
• Use advanced statistical, machine learning and AI methods to test methodologies proposed by the first line of defence
• Validate risk and financial valuation models, predictive models, machine learning models, NLP models, speech recognition models and generative AI solutions
• Assess model robustness, performance, stability, explainability and related risks, including algorithmic bias, model drift and responsible AI issues
• Help draft governance documents, methods and methodological and technological approaches
• Advise and train teams on quantitative model validation methods and help advance these methods
• Represent teams in dealings with internal stakeholders
• Monitor industry trends and anticipate emerging developments