Head of Decision Science Consulting, UK based

AI consultancy building capabilities in decision intelligence, semantic data systems and operational AI. This role leads the capability that transforms data and models into real operational decisions and measurable business outcomes.

Combining decision architecture, applied modelling and AI system integration, ensuring analytical work directly drives how organisations plan, price, forecast and operate. You will lead complex client engagements, shape the firm's decision science practice, working alongside AI engineering and consulting leaders to design, deliver and scale production decision systems.

What you will do

Client leadership - Lead high-value engagements in decision intelligence and AI-enabled operations, working directly with C-suite, data leaders, and operational heads. Translate complex business problems into decision systems with measurable outcomes across areas such as pricing optimisation, demand forecasting, risk and fraud modelling, resource allocation, and AI-enabled decision systems.

Build capability - Define and scale the firm's Decision Science practice. Create modelling frameworks, reusable components, and decision accelerators. Shape how modelling integrates with ontologies, semantic data platforms, and AI agents.

Design decision systems - Go beyond modelling to architect end-to-end decision systems combining data pipelines, ML models, business rules, semantic layers and AI agents, all Embedded in real workflows and operational systems.

Grow the business - Drive new client relationships and expand existing accounts through measurable value creation. Lead proposals, shape thought leadership and build market visibility in decision intelligence.

Lead the team - Mentor Decision Scientists and AI engineers. Set hiring standards, build delivery playbooks and contribute to a culture of high-agency, high-accountability builders.

What we are looking for

• 8+ years in decision science, data science, quantitative modelling, or operations research.
• Proven track record applying models in live business decision environments.
• Strong fluency in Python, modern ML tools, and decision optimisation frameworks.
• Deep understanding of statistical modelling and machine learning with experience deploying models into production-scale systems.

Beneficial: pricing and revenue optimisation, forecasting and supply chain, risk and fraud modelling, reinforcement learning, causal inference and experimentation.

Experience with AI systems, agentic architectures, or decision intelligence platforms is a strong advantage, as is consulting or senior client leadership experience.