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Montréal, CA

Internship

Hybrid

Intern

Desjardins Group is focused on maximizing the value of data to enhance member and client experiences. The Data Internship role involves assisting in information analytics, advanced analytics, machine learning operations, and data governance to support strategic decision-making and innovation in data valorization.

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Responsibilities

Help deepen our understanding of members and clients through data valorization and analysis to support strategic decision making
Create visual reports and issue recommendations to meet the needs of internal partners
Take part in exploring, evaluating and developing innovative AI methodologies and products to support data valorization
Help innovate and explore in one of our areas of expertise, like structured and unstructured synthetic data, generative and multimodal language models, etc
Help monitor new advances in AI and support their adoption by Desjardins Group
Work alongside data scientists and IT experts on a multidisciplinary squad to design, develop, deploy and monitor machine learning and AI systems
Help implement continuous integration and deployment (CI/CD) pipelines for machine learning models
Develop and maintain application programming interfaces (APIs) and software development kits (SDKs) that expose analytical models to applications in production
Document metadata in the information governance catalogue
Prepare content for metadata loading templates and update the catalogue and reference databases
Help data governance advisors classify metadata according to the current data architecture framework in a secure and private environment

Qualification

Required

Your educational institution must credit or certify your internship toward a bachelor's degree or a master's degree in an appropriate discipline
Knowledge of French required
Proficiency in software development, including object-oriented programming for machine learning operations
Knowledge of tools such as Tableau and Power BI for information analytics
Knowledge of SAS and SQL for information analytics
Knowledge of machine learning algorithms, deep learning and development frameworks (keras, tensorflow, pytorch, etc.) for advanced analytics
Knowledge of generative AI models and solutions (synthetic data, LLMs, prompt engineering, etc.) for advanced analytics
Knowledge of MS Office suite (especially Excel) for data governance