Applied AI​/ML Scientist

Join to apply for the Staff Applied AI/ML Scientist role at TELUS
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The AI Accelerator team is on a continuous journey towards helping TELUS become a world‑class leader in data solutions, delivering data analytics capabilities built upon unified scalable platforms, advanced AI solutions, high‑quality data, and a data‑product‑oriented culture while always keeping an eye on the horizon and preparing for the next big thing. We are entrepreneurial and live by our AI Manifesto of failing fast and being outcome‑driven, creating value for our customers, team members, communities, and the environment.

The team takes pride in our Artificial Intelligence and Machine Learning capabilities and takes ownership of each step of the process. From hypothesis generation and initial exploration of datasets to developing novel AI techniques, automation pipelines, and web visualizations, we do it all! If you want to work with a team of innovators across all business units within TELUS and be part of a culture that embraces creativity and collaboration, we’d love to talk with you.

• Lead the iterative development, validation, and deployment of AI/ML models across the organization, ensuring continuous improvement and scalability
• Drive the development and deployment of Generative AI applications, tools, and frameworks that solve critical business challenges
• Collaborate on end‑to‑end automation efforts required to bring machine learning models to production, ensuring smooth deployment and operationalization
• Work with both structured and unstructured data to design, develop, and deploy innovative predictive models, metrics, and dashboards that deliver actionable insights
• Visualize and report findings creatively through various formats (e.g., dashboards, interactive reports) to ensure insights are easily understood and actionable for stakeholders at all levels
• Influence strategic decision‑making and drive the adoption of a data‑driven mindset across the organization by solving business challenges and uncovering new opportunities
• Develop reusable code and solutions to accelerate future goals and deliver results faster and more reliably
• Support the evolution of data science and AI products by influencing product roadmap through prioritizing features to meet business needs, recommending latest industry research, tools, and best practices
• Build and maintain strong engagement with key stakeholders, understanding their business needs and priorities, and presenting AI/ML initiatives to VP‑level executives and beyond
• Serve as a functional leader of AI/ML across the company, providing technical leadership for the overall AI/ML program and collaborating with broader business units to scale AI/ML solutions
• Establish best practices for ML model deployment and production, ensuring models are scalable, reliable, and optimized for long‑term success
• Represent the company as a thought leader in the AI/ML space, presenting at conferences, publishing papers, and engaging with external forums to build TELUS’s reputation as a global leader in data science and AI
• Coach and mentor a growing team of data scientists and engineers, fostering a culture of continuous learning and innovation, and identifying future leaders within the organization

• Minimum 7–10 years of hands‑on experience in machine learning, AI, and data analysis, including deployment of solutions in business workflows
• Strong expertise in Python and experience with data science libraries (e.g., scikit‑learn, pandas, numpy)
• Solid background in machine learning algorithms, including regression, classification, clustering, time‑series analysis, reinforcement learning, and optimization
• Experience building and deploying Generative AI applications and workflows
• Proficiency in SQL and distributed computing
• Hands‑on experience with cloud platforms such as GCP, AWS, or Azure
• Expertise in machine learning frameworks such as Tensor Flow, PyTorch, and Keras
• Strong understanding of software and AI development life cycles, with experience in Dev Ops and MLOps practices
• Understanding of version control systems (e.g., Git) for collaborative…