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
- Data Scientist building IFRS 9, behavioural, and predictive credit-risk models for Financeit’s Canadian point-of-sale financing platform. Automating analytics and translating borrower data into actionable risk insights.
Responsibilities
- Build, validate, and refine sophisticated risk machine learning and statistical models across consumer credit, fraud, portfolio risk, and borrower behaviour
- Develop and enhance IFRS 9 models, including expected credit loss, probability of default, loss given default, exposure at default, and related risk forecasting and segmentation methodologies
- Build behavioural and predictive models using customer, transaction, portfolio, and macroeconomic data
- Build sophisticated yet explainable models connecting data to real-world events and customer behaviours to inform business decisions
- Translate complex analytical problems into scalable modelling solutions while balancing statistical rigour, interpretability, business impact, and practical implementation
- Identify high-quality, well-managed data sources and opportunities to apply automation, data pipelines, machine learning, and AI
- Participate in strategic projects and partner with cross-functional teams to support resourcing for modelling and reporting
- Document models, methodologies, policies, strategies, datasets, and tools using tools such as Confluence
- Experiment with new modelling techniques, analytical approaches, automation tools, and emerging technologies
- Work under the direction of the Director – Risk Analytics, Data Science & Reporting to deliver risk models supporting credit decision-making, portfolio management, and risk measurement
Requirements
- University degree in Engineering, Math, Computer Science, Applied Math or Applied Sciences, Finance, or another quantitative discipline
- 0–3 years of full-time and/or internship/PEY experience in analytics, data science, risk management, finance, or a related quantitative field
- Foundational experience with Python, SQL, Excel, or similar analytical tools; experience building models, working with data, or automating processes is a strong asset
- Exposure to machine learning, statistical modeling, credit risk, IFRS 9, behavioural modeling, or financial modeling would be a strong asset
- Strong pragmatic quantitative thinking, judgment, communication (verbal, visual, and written), with a demonstrated ability to break down complex problems and explain your work
- Curious and eager to learn, with the ability to dig into data, question assumptions, and develop an understanding of how models behave in the real world
- Highly organized and driven, with the ability to manage competing priorities while meeting deadlines
- A balanced sense of confidence and humility, with the ability to thrive in a collaborative environment and bring energy and enthusiasm to team culture
- Capable of having fun while doing all of the above; we’re serious about this
- All employment offers are contingent upon a successful background and credit check, among other verifications
Benefits
- An award-winning culture with a collaborative & inclusive team
- Competitive pay and performance-based bonus
- Annual Bonus: 20%
- Committed to flexible work arrangements, offering hybrid workplace options
- Comprehensive medical, dental and vision coverage + Lifestyle Account
- RRSP Matching and Parental Leave Top UP Program
- In office massage, meditation & workout sessions
- Virtual events such as Lunch & Learns, company parties, fun team activities and charity initiatives
- Career learning and development programs
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