Data Scientist - Virtual Position

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