Director of Platform, AI & Data

Director of Platform, AI & Data

Experian Nottingham, England, United Kingdom

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Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland.

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Reporting to the CTO with a dotted line into the CPCO, this role owns the strategy and execution across Product and Engineering for three core domains:
Platform, AI, and Data. Accountable for creating, maintaining, and socialising compelling, prioritised roadmaps that align platform and capability supply with product demand, while influencing the product roadmap with clear opportunity, cost, and risk signals. Responsible for adoption and internal sentiment as primary success measures, ensuring we only build capabilities that teams actively use and value. Leads UK and Hyderabad (India) teams and partners, balancing change and run, legacy and modernisation, buy/build/partner choices, and security and compliance requirements.

• CTO & Technology SLT
• CPCO, Product Leadership & stream-aligned product engineering teams
• Director of Strategic Insights & Analytics teams
• Senior Engineering ICs - Principal / Staff Engineers, Architects
• Marketing Leadership & teams
• Info Sec, Risk (2
  
  LOD), and Compliance
• Finance (budget, Fin Ops), Procurement, and Vendor partners
• UK&I BUs and global counterparts for reuse and interoperability

Product and Portfolio

• Own and socialise a rolling 4-quarter capability roadmap across Platform, AI, and Data; align capacity to product demand and business outcomes.
• Define and track adoption and internal sentiment targets for all capabilities; publish scorecards and retrospectives.
• Operate a transparent intake and prioritisation process balancing regulatory, reliability, and growth opportunities.
• Influence product roadmaps by evidencing platform leverage, reuse, cost-to-serve, and time-to-market impacts.
• Drive clear buy vs. build vs. partner decisions with measurable value and risk trade-offs.

Platform

• Deliver internal platform capabilities that simplify and accelerate product delivery: optimisation, feature toggles, personalisation, alerting, BAU support, and paved-road developer experience.
• Productise platform services and complex subsystems with SLAs/SLOs, APIs, documentation, and clear ownership; reduce cognitive load on product teams.
• Standardise observability, deployment, and release practices; improve lead time, change failure rate, MTTR, and availability.
• Promote reuse across UK&I and global BUs; retire obsolete services and reduce technical complexity.

AI

• Shape the AI domain and establish an AI-forward engineering culture with safe-by-design guardrails, patterns, and SDKs.
• Enable domains to build AI capabilities from within (assistive coding, test generation, summarisation, routing, risk checks) to do more with the same.
• Define model selection, evaluation, and monitoring practices; align with Responsible AI, privacy, and security standards.
• Measure AI adoption and productivity uplift; prioritise use cases with clear ROI and risk controls.
• Build out AI capabilities to power intelligent consumer experiences, including on- and off-property chat integrations to enhance user engagement and service efficiency.

Data

• Execute the data strategy and evolve a best-in-class data ecosystem supporting analytics and ML.
• Embed a data-as-a-product mindset with data contracts, lineage, quality SLAs, and clear ownership in domains.
• Advance data democratisation via self-serve tooling, secure access controls, documentation, and enablement.
• Modernise pipelines and platforms; manage the team through change while maintaining reliability and compliance.
• Lead geographically distributed teams; grow Hyderabad capability and manage third parties to outcomes.
• Coach Product and Engineering leaders across your domains to drive a high-performance culture and inspire teams.
• Own engineering excellence practices and continuous improvement across SDLC and incident management.
• Partner with Risk, 2
  
  LOD, and Security to meet regulatory and audit requirements without slowing delivery.
• Own budget for the three domains and drive Fin Ops, cost transparency, and unit-economics improvements.
• Occasional travel to…