Lead Data Scientist – Workday Products

Overview

In this Lead Data Scientist role within Kainos’ Workday products division, you will drive the design and delivery of advanced AI/ML solutions across the Workday product suite. You will collaborate with customers and mentor the team, providing strategic technical leadership. You will build robust, production-grade pipelines with MLOps and integrate AI into enterprise workflows. You will explore generative AI use cases and cloud-native architectures to scale solutions. You will contribute to a culture of collaboration and innovation while shaping the future of Workday solutions.

Responsibilities

• Lead design and delivery of advanced AI/ML solutions for the Workday product suite
• Collaborate with customers and stakeholders
• Mentor and manage data science team including performance appraisals
• Develop production-grade pipelines with MLOps practices and CI/CD
• Integrate AI/ML solutions with enterprise systems such as Workday
• Explore generative AI use cases (LLMs) for tasks like conversational AI and content creation
• Lead, guide, and provide thought leadership across the organization
• Create interactive dashboards and visual analytics to communicate insights
• Support career development and progression of team members

Key requirements

• 8+ years of relevant industry experience or PhD plus 4-5 years industry experience
• Strong Python programming for scalable AI/ML solutions
• Extensive experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch)
• Experience designing and maintaining production-grade AI/ML pipelines and MLOps (CI/CD, model versioning, monitoring)
• Experience with containerisation/orchestration (Docker, Kubernetes)
• Cloud experience (AWS/Azure/GCP) with tools like SageMaker, Vertex AI, Azure ML Studio
• Experience with generative AI use cases and LLMs (OpenAI GPT, Hugging Face Transformers)
• Data engineering, wrangling, and production pipeline creation
• Experience with Workday integration and enterprise systems
• Strong interpersonal and client-facing communication skills
• Leadership and formal line-management experience

• Strong communication and stakeholder management
• Mentoring and people development
• Collaborative, cross-functional collaboration
• Python
• Scikit-learn
• TensorFlow

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