Data Scientist - Virtual Position
Toronto, ON, CA, M5J 2V5 Edmonton, AB, CA Vancouver, BC, CA Ottawa, ON, CA Calgary, AB, CA
Description
Join our team
This is an exciting opportunity to join the CSD AI Innovation Hub within Customer Solutions Delivery (CSD). We are a dynamic and agile team revolutionizing field operations by designing data-driven AI solutions that optimize OpEx, CX, sales, billing, and other key metrics across our national technician workforce. Our AI Hub is the go-to destination for autonomous, creative professionals passionate about developing their talents while solving some of TELUS's most significant challenges.
As part of our team, you'll contribute to high-visibility programs that are transforming the telecommunications business model.
What you’ll do
As a Senior Data Scientist focused on delivering generative AI solutions, you will work cross-functionally to discover high-impact opportunities, tapping into diverse data sources to drive innovation across the business. Drawing on your expertise as a data scientist and a strong foundation in data engineering and software development, you’ll architect and implement scalable, end-to-end AI systems that support faster, smarter decision-making and accelerate enterprise AI adoption.
Your responsibilities will include:
- Design and deploy GenAI solutions (RAG, summarization, classification, intelligent agents) tailored to internal business needs
- Fine-tune open-source and proprietary foundation models (OpenAI, Claude, Mistral, LLaMA) on TELUS-specific data
- Integrate LLMs and multimodal models into production systems in collaboration with data engineers and developers
- Apply prompt optimization techniques (e.g., compression, chain-of-thought, few-shot, tool use) to balance cost, latency, and performance
- Evaluate model outputs using qualitative and quantitative methods (BLEU, human-in-the-loop feedback)
- Translate complex business problems into scalable, responsible GenAI and ML-driven solutions
- Contribute to internal tooling, standards, and reusable components for accelerating GenAI adoption at TELUS
- Maintain working knowledge of classical ML techniques (regression, clustering, tree-based models) for hybrid solution development
Qualifications
What you bring
- Master’s degree in CS, Machine Learning, Data Science — or a PhD in a relevant discipline
- 3+ years of experience applying ML/AI in business or production environments
- Proven expertise in working with modern LLMs (e.g., GPT-4, Claude, LLaMA, Falcon, etc.)
- Hands-on experience with vector search and RAG architectures
- Familiarity with fine-tuning tools and techniques (e.g., LoRA, PEFT, DeepSpeed, etc.)
- Strong development experience with Python and proficiency with data science libraries (Scikit-learn, Pandas, Numpy) and frameworks like TensorFlow, PyTorch, and Keras
- Solid understanding of MLOps best practices and model deployment via GCP (Vertex AI, Cloud Functions, Pub/Sub, etc.)
- Comfort working with unstructured data (text, PDFs, transcripts, emails) and embedding techniques (OpenAI)
- You are agile and have a bias for action, removing roadblocks to get results fast
- Excellent communication and documentation skills for both technical and non-technical audiences