Role Overview

As a Data scientist assigned to the Finance function, you play a key role in the technological aspect of Finance’s approach to innovation. You work directly with business teams to transform pain points, needs and opportunities, which are sometimes poorly defined, into concrete solutions by leveraging artificial intelligence, advanced analytics and automation. Your strength lies in building quickly and proving value. You’re comfortable in situations where the solution isn’t predefined and can quickly move from understanding a problem to creating a functional prototype. You design proofs of concept, pilots and minimum viable products (MVPs) in short cycles to test hypotheses and quickly inform the decision to continue, adjust, pivot or stop. You contribute, in particular, to developing and experimenting with new solutions using generative AI and AI agents. You also act as an artificial intelligence expert advisor for the Finance community, working closely with the Innovation team. Solutions that have demonstrated their value are then prepared for production with the relevant teams. More specifically, you will be required to: Understand and structure sometimes ambiguous business problems, then identify and qualify, with the relevant teams, use cases with high potential for the application of AI, advanced analytics, and automation. Assess the technical feasibility, business value and adoption potential of the proposed solutions to focus efforts on the most promising initiatives. Quickly design and develop prototypes, proofs of concept, pilots, and MVPs in short cycles of a few weeks to test hypotheses, measure their value, and determine whether to continue, adjust, pivot or stop. Develop artificial intelligence and data science solutions, including models,



algorithms and solutions using generative AI, large language models (LLMs), AI agents or other relevant approaches depending on the problem to be solved. Integrate various technologies, models, APIs and data sources to quickly build functional prototypes and concretely demonstrate their potential to users. Explore, experiment with and compare new AI technologies and approaches in a rapidly evolving technological environment to inform choices and application possibilities within the Finance function. Analyze and leverage financial and operational data to support experimentation, identify trends, risks and optimization opportunities, and inform the development of solutions. Work directly with business teams, explain the possibilities and limitations of technologies plainly, support experimentation with users, and serve as an AI resource person for the Finance community. Ensure the responsible, secure and compliant use of data and AI solutions, in alignment with the organization’s guidelines. Prepare solutions that have demonstrated their value for production and scaling by documenting lessons learned, success factors and technical requirements, in collaboration with the relevant teams.

Key Responsibilities

- Understand and structure sometimes ambiguous business problems, then identify and qualify, with the relevant teams, use cases with high potential for the application of AI,



advanced analytics, and automation.
- Assess the technical feasibility, business value and adoption potential of the proposed solutions to focus efforts on the most promising initiatives.
- Quickly design and develop prototypes, proofs of concept, pilots, and MVPs in short cycles of a few weeks to test hypotheses, measure their value, and determine whether to continue, adjust, pivot or stop.
- Develop artificial intelligence and data science solutions, including models, algorithms and solutions using generative AI, large language models (LLMs), AI agents or other relevant approaches depending on the problem to be solved.
- Integrate various technologies, models, APIs and data sources to quickly build functional prototypes and concretely demonstrate their potential to users.
- Explore, experiment with and compare new AI technologies and approaches in a rapidly evolving technological workplace to inform choices and application possibilities within the Finance function.
- Analyze and leverage financial and operational data to support experimentation, identify trends, risks and optimization opportunities, and inform the development of solutions.
- Work directly with business teams, explain the possibilities and limitations of technologies plainly, support experimentation with users, and serve as an AI resource person for the Finance community.
- Ensure the responsible, secure and compliant use of data and AI solutions, in alignment with the organization’s guidelines.
- Prepare solutions that have demonstrated their value for production and scaling by documenting lessons learned, success factors and technical requirements, in collaboration with the relevant teams.

What we offer

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📌 Data scientist (Montreal)
🏢 Federation Caisses Desjardins
📍 Montreal