ClearScore Technology Limited - Senior Knowledge Manager IC4

• 1. Produce a roll out a written Knowledge Strategy: Endorsed by the executive, this should explicitly address how we do knowledge management in an AI-enabled world. • 1. Produce a roll out a written Knowledge Strategy: • 2. Separate knowledge from working documents: Define what counts as knowledge for the Group (content that is authoritative, owned, current and worth trusting) versus working documentation such as drafts, scratchpads, meeting notes and in-flight thinking, set a higher bar for publishing to the knowledge corpus and use LLM-based tools to help enforce it. • 2. Separate knowledge from working documents: • 3. Actively maintain the corpus: Set review cycles, ownership and freshness expectations across the corpus and run the rhythm that keeps them honest, surface and resolve stale, duplicate or contradictory content (using LLM-based tools to scan for out-of-date facts, flag contradictions and identify duplicates across thousands of pages), treat decommissioning as a first-class activity with a credible first pass at the existing estate inside six months, maintain clear lineage, and work with Legal, Risk and Compliance on access, retention and regulator-facing obligations across our markets. • 3. Actively maintain the corpus: • 4. Fill the gaps in critical domains: Map the domains across the Group, identify where authoritative knowledge is thin or missing, and work down a prioritised backlog through a federated maintainer model where each significant domain has a named expert and a named maintainer working to a standard you set and a cadence you run, sitting alongside teams during the moments that generate important knowledge such as launches, incidents, regulatory responses and M&A so the output is captured at the time, not retrofitted later. • 4. Fill the gaps in critical domains: • 5. Make compounding learning a habit: Establish a simple, mandatory pattern for every significant piece of work to leave behind structured learning (what was the question, what did we decide, what happened, what would we do differently), make that the default output of quarterly business reviews, retros, incident washups, experiments and major decisions rather than a separate task that gets dropped, and curate the resulting record so it is actually retrievable later by people and by AI tools. • 5. Make compounding learning a habit: • 6. Equip our knowledge for AI consumption: Be the person who understands, in practical terms, how modern AI systems consume organisational knowledge (retrieval, structure, metadata, permissions) and who specifies what good looks like from the knowledge side, working with the AI Lead, Chief Architect, Chief Data Officer and Engineering on how knowledge is indexed, retrieved and served into internal AI tools (you own the content and its structure; they own the systems that consume it). You are not expected to build production retrieval systems yourself, but to know enough to make sensible design decisions, write the requirements, and spot when an AI answer is grounded in the wrong source. • 6. Equip our knowledge for AI consumption: • 7. Roll your sleeves up: Author and maintain the Group's canonical knowledge index: the single place any employee or internal AI tool goes to find the authoritative source on a topic. • 7. Roll your sleeves up: