We are seeking a highly skilled and innovative Data Scientist with hands-on experience in Generative AI (GenAI), Gemini, and cloud migration. The ideal candidate will have a strong foundation in Python programming, database management, and experience deploying solutions from on-premises infrastructure to the cloud (preferably Google Cloud Platform, but AWS or Azure are acceptable). This role involves developing intelligent data-driven solutions, building and deploying ML/GenAI models, and modernizing legacy systems by transitioning them to the cloud.

REQUIRED QUALIFICATIONS

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 3+ years of professional experience in data science or machine learning roles.
• Proven experience with Generative AI frameworks, including Gemini, GPT-based models, or similar technologies.
• Proficiency in Python for data manipulation, machine learning, and system automation.
• Strong experience deploying AI/ML models and data solutions to cloud platforms (GCP preferred; AWS/Azure acceptable).
• Solid experience with on-premises environments and migrating code/solutions to the cloud.
• Expertise in SQL and NoSQL database design, management, and performance tuning. Experience with version control (e.g., Git), containerization (e.g., Docker), and orchestration tools (e.g., Kubernetes) is a plus.
• Strong problem-solving skills and ability to work independently and in teams.

PREFERRED QUALIFICATIONS

• GCP certifications (e.g., Professional Data Engineer or ML Engineer) or equivalent in AWS/Azure.
• Familiarity with MLOps and DevOps workflows.
• Experience working with BigQuery, Vertex AI, or other cloud-native AI/ML tools.
• Strong understanding of data governance, security, and compliance in cloud environments.
  Job Type: Fixed term contract

Schedule:

• Monday to Friday

Work Location: Hybrid remote in Verdun, Q

• Design, develop, and implement advanced analytics and Generative AI models using tools such as Gemini and other LLM frameworks.
• Build scalable data science workflows and pipelines in Python.
• Deploy, monitor, and maintain machine learning and AI solutions in cloud environments (preferably GCP, but AWS or Azure acceptable).
• Lead the migration of models, data pipelines, and analytics platforms from on-prem environments to cloud infrastructure.
• Collaborate with cross-functional teams to integrate AI/ML models into production systems.
• Manage relational and non-relational databases, including optimization and data integration.
• Ensure best practices in model versioning, reproducibility, testing, and deployment (CI/CD).
• Document data science solutions and communicate technical findings to non-technical stakeholders.