Senior Consultant, Data Science & AI

Key responsibilities

• Develop Machine Learning Models: End-to-end development, training, and deployment of production-grade predictive and prescriptive models (e.g., propensity modeling, customer segmentation, demand forecasting).
• Design & Deploy Generative AI Solutions: Architect, fine-tune, and evaluate enterprise Gen AI systems—including Retrieval-Augmented Generation (RAG) pipelines, custom LLM applications, and prompt engineering frameworks—to extract insights from unstructured data.
• Architect Agentic AI Systems: Design and deploy autonomous AI agents and multi-agent workflows capable of multi-step reasoning, tool utilization, and task automation to solve complex client business challenges.
• Deliver Advanced Analytics: Help clients maximize the efficiency of their strategic initiatives by building advanced analytics models that measure campaign performance, predict customer behavior, and maximize long-term ROI.
• Data Storytelling & Visualization: Synthesize complex algorithmic outcomes and machine learning metrics into compelling, executive-ready presentations and dashboards that clearly articulate business value and ROI.
• Develop and Maintain Analytics Workflows: Analyze raw client data and build optimized analytics datasets within cloud environments to support modeling and reporting.
• Lead workshops with external clients to uncover business objectives, map out data landscapes, and translate vague business problems into structured data science methodologies.
• Create solutions and design documentation for client data science architectures and ML pipelines.
• Work on projects independently as well as being part of a large team across multiple client engagements.
• Crosstrain Junior Data Scientists/Analysts or other team members with your area of expertise, providing technical leadership and code reviews.
• Further develop skills both on the job and through formal learning channels to stay ahead of AI/ML trends.
• Assist in pre-sales activities by scoping new client opportunities and providing accurate work/effort estimates.

Skills and Experience Requirements

• Post-Secondary Degree (or Diploma) related to Data Science, Statistics, Computer Science, Economics, Business Analytics, or an IT-related field.
• 5–8 years of total experience in Data Science, Advanced Analytics, or Management Consulting.
• 3+ years of experience in an external client-facing consulting or professional services capacity.
• 3+ years of application, model design, and deployment experience natively within a cloud environment (GCP preferred).
• 1–2+ years of hands-on experience architecting and deploying Generative AI systems (e.g., RAG pipelines, fine-tuned LLMs) and Agentic AI workflows (e.g., autonomous agents, tool-use integration).
• Demonstrated experience delivering both traditional predictive models and modern AI solutions to enterprise stakeholders.
• Google Cloud Certified Professional Data Engineer, Professional Machine Learning Engineer, or equivalent Generative AI/Cloud Certifications (Highly Preferred).
• Python Stack: pandas, numpy, scikit-learn, XGBoost, PyTorch/TensorFlow, Transformers
• Generative & Agentic AI Frameworks: LangChain, LlamaIndex, AutoGen/CrewAI, Prompt Engineering, RAG architectures, Multi-Agent Orchestration, Function Calling & Tool Integration
• Vector Databases & Search: BigQuery Vector Search, Google Cloud Vector Search, Pinecone, Chroma, or FAISS
• SQL: Advanced query optimization for large-scale data warehouses
• Google Cloud Platform (Core focus): Gemini Enterprise, Vertex AI Agent Builder, BigQuery ML, Model Garden (Model development, fine-tuning, and deployment)
• Data Engineering & Orchestration: BigQuery, Dataflow, and Cloud Storage for data extraction, pipeline management, and indexing
• BI & Data Visualization Tools: Looker / Looker Studio, Tableau, or Power BI
• MarTech/AdTech Ecosystems
• Agile/Scrum Methodologies
• CI/CD & MLOps/LLMOps: Version control, automated deployment pipelines, LLM evaluation, and model monitoring tools
• Personal: Strong interpersonal skills, high energy and enthusiasm, integrity, and honesty; flexible, results-oriented, resourceful, structured problem-solving ability, deal effectively with difficult client situations, ability to prioritize.
• Leadership: Ability to gain credibility, motivate, and provide leadership; work with a diverse external customer base; maintain a positive attitude. Provide technical support and guidance to more junior team members, particularly for challenging modeling or analytical assignments.
• Operations: Commercial acumen and ability to manage multiple projects simultaneously. Perform tasks in a client-friendly manner while utilizing time and resources efficiently, proactively managing project scope.
• Technical: Ability to understand, translate, and communicate highly complex technical and mathematical concepts to non-technical business stakeholders.

Salary

130,000 – 160,000 CAD per year

Employment type

Full-Time