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
- Lead Data Scientist responsible for designing and deploying Generative AI solutions. Collaborating closely with clients and mentoring teams in analytics consulting at Tiger Analytics.
Responsibilities
- Work on the latest applications of data science to solve business problems.
- Work directly with client stakeholders to translate business problems into high level analytics solution designs.
- Present analytic solutions to business audiences highlighting robustness of the solution and how it could help generate business value.
- Develop end-to-end solutions based on in-depth understanding of business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably.
- Design and develop machine learning and Generative AI solutions using RAG.
- Build LLM-powered applications leveraging Azure OpenAI and orchestrate workflows using LangGraph.
- Develop agentic AI workflows for automation, insights generation, and decision support.
- Implement Document Intelligence solutions for extracting insights from unstructured data.
- Participate in discussions with team members to select and apply relevant analytic techniques and create actionable business insights.
- Responsible for making presentations to senior management, communicating results to business teams, and develop plans to help operationalize analytic solution.
Requirements
- 7+ years of experience working as a GenAI Data Science.
- Proficiency in Python and SQL.
- Experience with MLflow and model lifecycle management.
- Experience with Python from a functional programming paradigm, able to manage dependencies and virtual environments, along with version control in git.
- Generative AI Knowledge: Solid understanding of latest-generation AI concepts including LLMs, prompt engineering, retrieval-augmented generation (RAG), and other contemporary generative AI applications.
- Experience with sequential algorithms (e.g., LSTM, RNN, transformer, etc.).
- Experience with Bedrock, JumpStart, HuggingFace.
- Experience evaluating ethical implications of AI and controlling for them (e.g., red-teaming).
- Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning.
- Experience in generative algorithms (e.g., GAN, VAE, etc.) as well as pre-trained models (e.g., LLaMa, SAM, etc.).
- Experience developing models from inception to deployment 5-10 years of professional work experience with at least 5 years in Data Science.
- Experience building end-to-end ML pipelines in production.
- Familiarity with CI/CD pipelines, monitoring, and model governance.
- Ability to design scalable and reliable AI systems.
- Bachelor's in Business Analytics or equivalent work experience.
Benefits
- Significant career development opportunities exist as the company grows.
- Unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
- Equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
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