What I do
Experimentation strategy
Building and scaling A/B testing programmes — from experiment design and statistical rigour through to cultural adoption across product teams.
Product analytics
Defining metrics, building dashboards, running deep-dive analyses. Turning product data into decisions rather than reports.
Interim leadership
Covering analyst lead roles during hiring gaps, mat leave or organisational change. Hands-on from day one.
Background
Most recently at Reach plc — one of the UK's largest digital publishers — where I spent nine years across a range of roles, moving from content and operations into data and experimentation over time. The last four years were product-facing: designing and analysing A/B tests, investigating user behaviour with BigQuery and Athena, and turning results into recommendations for product managers and senior stakeholders.
Practically: I owned end-to-end experiment analysis across 65+ national and regional titles — producing go/iterate/stop readouts across registration prompts, content gating, and engagement initiatives, contributing to a ~5% uplift in yearly pageviews worth an estimated £50K+ in incremental ad revenue. I designed a painted door experiment to quantify subscription appetite at segment level, providing paywall strategy teams with concrete demand signals where none had previously existed. I evaluated 10–20 experiments per month, built Looker Studio dashboards for behavioural monitoring, and analysed feature rollouts — including a Bookmark feature whose case I helped make, which shipped and remains live today.
Outside my analyst career, I've spent over two decades researching Socionics and have built several independent projects from scratch: Socion (a full-stack matching app in React and Supabase), Socionics Insight (a 372-page reference site), and a 17-book series. I mention this because it's directly relevant to how I work: I'm used to owning problems end-to-end, directing tools rather than waiting for direction, and shipping things in production rather than in decks.
I'm comfortable directing AI tools for analysis work — guiding code generation and interpreting output — which is how most practical analytics work gets done now.
What I'm looking for
Permanent and fixed-term analyst roles at large tech companies — ideally organisations that already have a testing culture and want someone to deepen it, rather than those starting from scratch. I work best where data is genuinely upstream of product decisions, not a reporting afterthought, and where an analyst is expected to push back on a poorly-designed test before it runs.
Based in London. Remote-first, open to hybrid.