Manager Data Science

Are you ready to lead the teams building AI that helps advance science?

Are you motivated to shape AI and data science strategy that drives meaningful impact across products, customers, and business outcomes?

Would you enjoy leading teams to build advanced AI systems that power knowledge discovery and innovation at scale?

About our Team

Our global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality.

About the Role

In this role, you will define and lead AI and data science strategy across machine learning, NLP, search, and generative AI to deliver impactful, scalable solutions. You will guide teams through the full lifecycle of AI systems, from experimentation to production, while aligning work to product goals and customer needs. You will also influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation.

Responsibilities

• Set AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI, aligning work to product goals, customer needs, and business priorities.
• Lead and develop high-performing teams by coaching talent, setting priorities, fostering scientific rigor, and building an inclusive, collaborative culture.
• Deliver advanced AI and knowledge-discovery systems across the full lifecycle, from experimentation through production, including LLMs, RAG, search, and domain-enriched AI solutions.
• Drive evaluation and AI quality by establishing robust frameworks, metrics, experimentation practices, and responsible AI standards.
• Influence across product, technology, and business by partnering with cross-functional leaders, shaping roadmaps, translating technical insights, and aligning teams on customer and business impact.

Requirements

• Significant experience in data science, AI/ML, NLP, information retrieval, statistics, or a related quantitative field, or equivalent practical experience.
• Strong technical expertise across modern data science methods, including machine learning, experimentation, deep learning, generative AI, and production AI systems.
• Hands-on experience delivering AI-powered products, including LLMs, RAG, semantic search, embeddings, agentic workflows, and knowledge-driven systems.
• Proven success leading and developing technical teams in complex product, platform, or research environments.
• Experience working with large, complex datasets and building scalable, maintainable, production-ready AI/ML systems.