Data Scientist II

Summary

The successful candidate will hold a key role within the Consumer Business Intelligence (CBI) group, acting as the technical lead and primary AI capability builder for a highly delivery focused team. In this hands-on capacity, you will guide the shift from AI experimentation to production deployment by delivering priority use cases and establishing robust engineering standards across the vertical.
Operating at the forefront of applied artificial intelligence, you will provide technical guidance and direction to the broader team on AI solutioning and architecture. This role requires an intense focus on building and deploying scalable agentic workflows, machine learning models, and integrations across our enterprise stack to unlock immediate business value.

Key Responsibilities

• Design, build and deploy end-to-end production artificial intelligence solutions to address priority business needs
• Develop agentic workflows and multi-agent orchestration on enterprise platforms including Gemini Enterprise, AWS Bedrock and Azure AI Foundry
• Architect and optimize retrieval-augmented generation pipelines including chunking, embedding, vector store design and grounding
• Lead machine learning model development from initial feature engineering through evaluation, explainability and production monitoring
• Establish rigorous engineering standards covering Git workflows, code review, repository structure, testing, continuous integration and deployment
• Build robust data and integration pipelines connecting enterprise systems including Teradata, BigQuery and Salesforce
• Provide technical leadership and hands-on guidance to upskill team members on advanced artificial intelligence techniques
• Partner with business intelligence stakeholders to assess feasibility, effort, risk and value for incoming use cases
  Implement responsible evaluation practices encompassing accuracy testing, hallucination guardrails, human-in-the-loop controls and cost monitoring
  Maintain a continuous awareness of the rapidly evolving technological landscape to introduce new capabilities to the team

Critical Qualifications

• Bachelor’s or Master’s degree in computer science, data science, engineering, statistics or a related field
• 2 or more years of hands-on data science, machine learning or AI engineering experience with demonstrated production delivery
• Advanced proficiency in Python and SQL with extensive enterprise data warehouse experience such as Teradata
• Demonstrated hands-on generative AI delivery including agentic workflows and retrieval-augmented generation supported by a portfolio or practical experience
• Hands-on experience building solutions on at least one major cloud artificial intelligence platform
• Solid machine learning foundations with framework experience including scikit-learn, XGBoost, PyTorch or TensorFlow
• Deep expertise in Git-based development workflows and modern software engineering best practices
• Passion for maintaining a forward-looking mindset with a strong willingness to challenge conventional approaches to artificial intelligence
• Ability to work in a fast paced, dynamic environment and manage multiple projects through effective prioritization
• Ability to communicate effectively with all levels of the organization, including the ability to grasp complex AI concepts and explain them clearly to large non-technical audiences
• Strong data analytical and problem solving skills and demonstrated ability to be highly creative in formulating solutions

Preferred Qualifications

• Familiarity with cloud-based technologies and services, such as AWS or Google. Relevant certifications (e.g., Google & AWS Certified Solutions Architect, Google Cloud Generative AI Leader) are an asset
• Strong understanding of MLOps and LLMOps practices for deploying and managing models at scale
• Advanced modelling and optimization techniques such as constraint programming and operations research
• Experience with Salesforce, Tableau or comparable customer relationship management and business intelligence platforms
• Bilingual (French/English) is an asset
• Telco experience is considered an asset

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