HEAD OF DATA SCIENCE - Hybrid

Head of AI x34 days a week in the office (nearest station: This high-growth technology company has rapidly scaled a platform that blends on-demand solutions with intelligent optimisation. It helps thousands of businesses improve work management, service quality, and operational performance in real time.

After launching a new AI product that has already reached seven-figure annual recurring revenue within its first year, the business is now preparing for further UK expansion and a move into international markets. They are hiring a Head of AI / Data Science to take things to the next level. This person will lead technical direction, guide a growing team, and remain closely involved in delivering machine learning systems that power real-world impact across the platform.

Youll shape the roadmap, lead from the front, and play a key role in embedding intelligence into every aspect of product and strategy.

Set the overall AI strategy and ensure it connects clearly to product outcomes, user value, and business growth
Lead and support a team of Data Scientists and ML Engineers while maintaining a strong personal technical contribution
Design and scale ML solutions focused on forecasting, optimisation, and real-time performance enhancement
Build the infrastructure needed to support experimentation, training, and deployment of production-grade models
Work closely with Product, Engineering, and Commercial teams to ensure AI delivers measurable results
Act as the internal champion for intelligence, influencing how the company makes use of data and automation at every level

Circa 6-12 years of experience in ML, AI, or applied data science, with a track record of technical leadership
A strong academic foundation in a quantitative or technical subject, ideally including postgraduate study
Hands-on experience bringing ML systems from research through to live deployment
Strong Python programming skills and experience with libraries such as PyTorch, TensorFlow, or Hugging Face
Good understanding of infrastructure and deployment, ideally in cloud environments such as AWS
Exposure to areas such as time-series modelling, optimisation, computer vision, or reinforcement learning
Motivated by impact, scalability, and helping an organisation make intelligence a core capability