Transport AI & Data Strategy Lead (Hybrid, London)

Do you want to be at the heart of major AI & data-enabled transformation in transport (road, rail and aviation)?

Technology & Transformation

You’ll help senior leaders across transport organisations make intelligent, future‑proof decisions in a world where customer expectations, operations and regulation are continually evolving. You’ll build trusted relationships with senior business and technology stakeholders—often day‑to‑day—and use leading data, analytics and AI capabilities to design and deliver programmes that improve performance, resilience and customer outcomes.

Your role

• As a Senior Manager, you will shape and deliver AI, data and analytics engagements for transport clients, leading a workstream and supporting teams to deliver high‑quality outcomes.
• Combine strong problem solving with the ability to build rapport with stakeholders, coach others and thrive in ambiguity.
• Build strong relationships with client stakeholders, running workshops, capturing requirements and communicating progress clearly.
• Support end-to-end delivery of AI & data workstreams—helping shape the solution approach, managing workstream delivery, and ensuring day-to-day execution meets time, cost and quality expectations.
• Lead a small team or workstream (and/or manage junior colleagues), providing direction, quality assurance and coaching—with scope to take on broader people management as you progress.
• Conduct research and apply critical thinking to turn an initial idea into a structured, evidence‑based recommendation—demonstrating resourcefulness, proactivity and comfort working through ambiguity.
• Contribute to proposal development and practice initiatives where needed (e.g., drafting sections, creating supporting analysis and reusable assets), while maintaining focus on delivering excellent client outcomes.

Connect to your skills and professional experience

• Experience working in or consulting to the transportation industry (road, rail or aviation), with a strong understanding of sector drivers and operational realities.
• Strong track record leading complex AI, data, analytics or digital transformation initiatives from shaping through delivery, including robust governance and stakeholder management.
• Proven experience engaging senior stakeholders daily—building trust and rapport, influencing decisions, managing risks/issues and communicating clearly across business and technology audiences.
• Experience leading a workstream or small team and developing junior colleagues, with evidence of coaching, quality assurance and collaboration.
• Strong research and problem‑solving skills: able to take the kernel of an idea, work through ambiguity, and develop a viable answer or solution through structured thinking, analysis and stakeholder input.
• Relevant certifications are desirable, such as PMP; PRINCE2 (Foundation/Practitioner); MSP; APM PMQ/ChPP; Scrum Master (e.g., PSM/CSM) and/or agile practitioner certifications (e.g., PMI-ACP), and scaled agile certifications (e.g., SAFe).
• Working knowledge of AI technologies and approaches is desirable (e.g., Machine Learning (ML), Large Language Models (LLMs), Cloud Technologies and Generative AI), with the ability to engage credibly with technical teams and client stakeholders.

TECHNICAL / DELIVERY PROFICIENCY

• Experience shaping and delivering AI/ML and/or Generative AI solutions and use cases, from discovery and prototype through to deployment and adoption (in partnership with engineering teams).
• Understanding of modern AI/ML and GenAI concepts (e.g., LLMs, prompt engineering, RAG patterns and evaluation), with the ability to work effectively with technical teams and contribute to practical solution decisions.
• Working knowledge of data platforms and engineering (e.g., cloud data services, data pipelines, integration, SQL), and how these enable analytics and AI products in complex client environments.
• Experience establishing appropriate governance, risk management, security practices and ethical AI guardrails across the delivery lifecycle (including evaluation, privacy, model risk and operational controls).
• Broad experience across major cloud platforms (AWS, Azure, GCP) and their AI/GenAI services; cloud‑agnostic experience is preferred.
• Good grasp of MLOps/LLMOps practices (e.g., CI/CD, model/LLM monitoring, controls and auditability) and how to embed them pragmatically within client delivery.
• Familiarity with large‑scale data processing and storage technologies (e.g., SQL, Spark).
• Excellent communication and stakeholder management skills, including the ability to translate complex technical concepts for diverse business and technical audiences.

Location and Hybrid Working

You will be based in London with hybrid working. You may work in your local office, virtual collaboration spaces, client sites and remotely.