About the Role
We are seeking a visionary and pragmatic Sr. Director of Data Science & Machine Learning to lead our high-impact AI strategy and execution. This is a "builder-leader" role responsible for bridging the gap between cutting-edge research and production-grade software and operations. The Sr. Director will lead a team of Data Scientists, ML Engineers (MLEs), MLOps Professionals, and Full-Stack Engineers. The team will drive our data products from traditional predictive analytics into a modern, Agentic AI-driven ecosystem.
Job Responsibilities:
Strategic Leadership: Define the North Star for AI/ML initiatives, ensuring alignment with overarching business goals.
Multi-Disciplinary Management: Lead and mentor a diverse team of 15+ professionals across data science, engineering, and operations.
GenAI & Agentic Frameworks: Architect and oversee the deployment of LLM-based applications using RAG (Retrieval-Augmented Generation) and Agentic workflows.
Innovation Lab: Rapidly prototype new features using emerging tools (Hugging Face, Gemini, Claude) while maintaining a path to scalable production.
Product-Led AI Strategy: Work closely with Product Management to embed predictive insights and Agentic AI directly into custom solutions.
LLM Orchestration & Evaluation: Lead the implementation of Agentic workflows using solutions such as LangGraph and Flowise, ensuring reliability through rigorous evaluation frameworks like LangSmith.
Cost Management (FinOps): Optimize the cost of AI features by balancing the use of frontier models (Claude 3.5, Gemini 1.5) with smaller, fine-tuned open-source models via Hugging Face.
Stakeholder Influence: Act as a bilingual translator between complex technical architectures and executive-level business value.
About You
Basic Qualifications:
10+ years of professional experience across Data Science, AI and ML within an enterprise environment.
5+ years of professional experience within a senior leadership role.
Extensive experience moving Generative AI models from "notebook" to "production." Deep understanding of prompt engineering, fine-tuning, and agentic orchestration.
Experience with Snowflake, Databricks, AWS, GCP, H2O, Tecton, Hugging Face, Gemini, Anthropic Claude, Flowise, LangChain, LangGraph, LangSmith and other commercial and open source models and frameworks.
Experience with modern data stack patterns (Lakehouse, Data Mesh) and the specific challenges of MLOps (drift detection, latency, cost management).
Understanding of how ML models integrate with front-end applications via APIs (FastAPI, React).
Master’s or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please .
Primary Location: CAN.ON.TorontoPrimary CAN Base Pay Range: $247,000 - $370,400 CADAdditional CAN Location(s) Base Pay Range: $247,000 - $370,400 CADSr Director, Data Science & Machine Learning • Toronto, ON, Canada
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