Who you are

• We are seeking a visionary and pragmatic Sr Director of Data Science & Machine Learning to lead our high-impact AI strategy and execution
• 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

What the job involves

• The Enterprise Data and AI Technologies & Architecture (EDATA) organization is a dynamic and evolving team that is spearheading Workday’s growth through trusted data excellence, innovation, and architectural thought leadership
• Equipped with an array of skills in data & AI platforms and architecture, data science, engineering, machine learning and AI strategy & product management, this team orchestrates the flow of data across our growing company while ensuring data accessibility, accuracy, and security
• With a relentless focus on innovation and efficiency, Workmates in EDATA enable the transformation of complex data sets into actionable insights that fuel strategic decisions and position Workday at the forefront of the technology industry
• 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
• 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