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Data Science & AI Delivery Lead
City, London (Hybrid – 3 days per week)
£90,000 – 120,000 per annum, 15 – 20% bonus target
We’re looking for an experienced Data Science & AI Delivery Lead to lead the delivery of enterprise AI and machine learning solutions within a global insurance organisation.
This is a hands-on technical leadership role, ideal for someone who enjoys combining software engineering, data science, AI, and delivery leadership. You’ll help shape the technical direction of a growing AI function while leading the successful delivery of innovative solutions using machine learning, generative AI, and cloud technologies.
What you’ll do
- Lead the end-to-end delivery of AI, machine learning, and advanced analytics solutions from concept through production.
- Provide technical leadership across multiple AI initiatives, ensuring high standards for architecture, engineering, scalability, and deployment.
- Design and build AI solutions using large language models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI approaches.
- Remain hands-on with development, contributing to Python code, architecture reviews, and technical problem-solving.
- Drive best practices across MLOps, testing, deployment, monitoring, version control, and AI governance.
- Partner with engineering, data, and business teams to deliver scalable, production-ready AI capabilities.
- Mentor and develop a team of Data Scientists and AI Engineers through coaching, code reviews, and technical leadership.
- Evaluate emerging AI technologies and lead proof-of-concepts that create business value.
What we’re looking for
- Significant experience delivering AI and machine learning solutions in production environments.
- Strong Python development skills with experience across modern machine learning and data science frameworks.
- Hands-on experience with large language models, generative AI, prompt engineering, and RAG architectures.
- Experience with Databricks, MLflow, Spark, and cloud-based AI platforms (Azure preferred).
- Strong understanding of MLOps, software engineering best practices, and production deployment pipelines. xwwtmva
- Experience leading technical teams while remaining actively involved in solution delivery.
- Excellent stakeholder ma
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