How I Work
Analytics, AI tooling, and partner experience. Where I add the most value, how I collaborate, and what I am looking for next.
One-minute read
Download PDFI build analytics and data products, tooling, and AI workflows end to end: from finding problems with users and operators through data, logic, UX, and adoption. The AI decision-support platform grew to 199 users asking questions and 79 becoming regular users. I work best with clear goals, trusted scope, fast feedback, and colleagues who treat teaching and reusable patterns as part of delivery. I am looking for roles where I own analytics or data platform work end to end, with growth through mentoring and coordination toward leading a small specialist team.
At a glance
- Build across analytics, BI, data products, AI workflows, and UX end to end
- Anchor example: AI decision-support platform (199 users asked questions, 79 became regular users over 5 months)
- Work best with clear goals, trusted scope, and people close to the problem
- Looking for: end-to-end product ownership in analytics, data platforms, or AI tooling; growth through mentoring and coordination
What I build
I create value at the intersection of analytics, tooling, AI, and user experience. I build end to end: from finding problems with users and operators through data, logic, interface, and adoption. This spans analytics platforms and discovery hubs, BI and data tooling, conversational AI workflows, and operational reporting that changes decisions.
- Finding useful problems alongside users and stakeholders, then framing success by outcomes and adoption.
- Building end to end across data, business logic, tooling, UX, and rollout so solutions work in real workflows.
- Replacing fragmented, manual work with reusable systems and clear patterns others can extend.
- Teaching, documenting, and codifying reusable patterns so teams move faster on the next problem.
How I work
I do my best work with clear goals, trusted scope, and close collaboration with people who know the problem. I need room to ask whether the requested output is the right solution, then iterate with fast feedback after launch. Analytics is strongest when it connects to product thinking, UX, and tooling, not when it stops at one-off extracts or static decks.
- Clear goals and trusted scope so I can pursue the right problem, not just the first ticket.
- Regular access to stakeholders and users who can explain constraints and what success looks like.
- Permission to challenge briefs when a smaller change, tool, or interface would serve better.
- Short cycles from build to feedback, and time to improve what we shipped rather than only starting the next thing.
Evidence from recent work
The AI decision-support platform illustrates this pattern. Built as an analytics discovery hub and diagnostic engine, it reduces friction between question and trusted answer. Over five months (March to August 2026), 199 people asked at least one question and 79 became regular users. The platform routes questions, retrieves relevant data and docs, generates answers, and visualises results in one guided flow. It shipped with 93%+ answer success and under 0.5% error rate, saving roughly 90 analyst-hours in the final six weeks.
What's next
I am looking for roles where I can own analytics or data platform work end to end: building tools and systems that improve how people find, trust, and use data; scaling adoption; and improving decision quality. Titles like Analytics Product Lead, Data Product Lead, BI Platform Lead, or Analytics Engineering Lead describe the scope well. Growth for me comes through mentoring, coordinating small workstreams, and over time leading a small, high-skill group with complementary strengths in analytics, tooling, UX, and adoption.