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 at McKesson focusing on Generative AI and ML solutions. Address complex healthcare challenges and drive business transformation via innovative technology.
Responsibilities
- Lead the end-to-end lifecycle of Generative AI and agentic AI solutions, including ideation, research, prototyping, implementation, evaluation, deployment, and production support
- Architect and develop scalable GenAI systems such as LLM-based applications, Retrieval-Augmented Generation (RAG), AI agents, and intelligent automation workflows to improve decision-making, operational efficiency, and customer outcomes
- Drive adoption of best practices in prompt engineering, LLM evaluation, fine-tuning strategies, and secure model hosting where applicable
- Apply advanced data science and machine learning techniques across a wide range of use cases including predictive modeling, forecasting, classification, anomaly detection, recommendation systems, NLP, and GenAI-enabled analytics
- Develop custom ML models and analytical frameworks tailored to complex healthcare and enterprise data challenges
- Perform exploratory data analysis (EDA), feature engineering, and statistical analysis to generate actionable insights and guide solution design
- Collaborate with engineering and platform teams to deploy, monitor, and maintain ML and GenAI solutions in production environments using cloud-native and MLOps best practices
- Establish model performance tracking, drift detection, reliability monitoring, and continuous improvement processes for deployed models and AI agents
- Ensure solutions are scalable, cost-efficient, resilient, and aligned with enterprise architecture standards
- Ensure strong model governance, documentation, and auditability across all ML and GenAI solutions
- Apply Responsible AI principles including explainability, transparency, data privacy, security, and regulatory compliance, particularly within healthcare contexts
- Provide guidance on safe, compliant, and ethical use of LLMs and agentic AI across enterprise use cases
- Work closely with business stakeholders and product managers to translate requirements into clear analytical problem statements, solution designs, and execution roadmaps
- Present technical solutions, insights, and progress updates to both technical and non-technical audiences, including senior leadership
- Mentor and guide junior data scientists and engineers, fostering a culture of technical excellence, innovation, and continuous learning.
Requirements
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field
- 7–10+ years of experience in data science or advanced analytics, with significant hands-on experience in Generative AI and LLM-based systems
- Proven experience designing, building, and deploying production-grade ML and GenAI solutions, including LLMs, RAG architectures, and AI-driven automation
- Strong proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, and/or Hugging Face
- Deep understanding of machine learning algorithms, statistical modeling, experimental design, and data structures
- Experience working with cloud platforms (Azure preferred; AWS/GCP acceptable)
- Ability to clearly communicate complex technical concepts to diverse business and technical audiences
- Demonstrated leadership in driving projects, influencing stakeholders, and mentoring team members.
Benefits
- Competitive compensation package
- Health insurance
- 401(k) matching
- Flexible work hours
- Professional development opportunities
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