Lead Data Scientist

In this Lead Data Scientist role, you will drive end-to-end ML/AI projects from discovery to production, shaping Howden’s AI capabilities at scale. You’ll partner with business and engineering teams to identify opportunities, deliver production-grade solutions, and mentor others. You’ll act as a technical leader, setting best practices and helping translate complex analytics into business outcomes. This is a hands-on role with a strong business impact in a collaborative, employee-owned global organisation.

• reasonable adjustments
• flexible hours
• hybrid working

• Lead end-to-end delivery of ML/AI solutions from discovery to production and optimization
• Collaborate with stakeholders to identify opportunities and prioritise based on business value
• Design, develop, and deploy scalable ML, predictive analytics and AI applications
• Advise on best practices in DS, experimentation, model development, MLOps and software engineering
• Work with Data Engineering, Platform and Product teams to deliver production-grade solutions
• Help evolve Howden's AI/data science capabilities, standards and ways of working
• Support agile delivery teams with technical leadership throughout the product lifecycle
• Stay current with DS/AI/cloud developments and introduce innovative approaches

• Proven track record of building and deploying production-grade AI/ML applications with measurable business value
• Experience collaborating with Data Engineering, MLOps and Product teams to deliver ML systems end-to-end
• Excellent Python skills and hands-on use of XGBoost, PyTorch, TensorFlow or Hugging Face
• Experience with cloud-based data/AI platforms, especially Azure and Databricks
• Strong stakeholder engagement and ability to translate technical complexity into executive narratives
• Experience in agile cross-functional product/delivery teams
• Commercial mindset with focus on outcomes; insurance/financial services experience desirable
• Experience with Generative AI, LLM applications, agentic systems
• Mentoring/coaching experience for other data scientists or technical practitioners

• Stakeholder engagement
• Storytelling/communication
• Collaborative mindset
• Python
• XGBoost
• PyTorch