First product hire into a services business with ambitions to build SaaS. I took Ignite from an internal tool to a fully licensed SaaS platform used by 250+ brands, 15+ agencies, and 1,200 users, and took Texana from proof-of-concept to a shipped agentic GenAI product that cut a three-week reporting project to three days. I also owned the Ads Console, shipped AI/ML-powered bid optimisation with a typical 5x uplift for new brands, built LTV models using first-party data, and led internationalisation including Japanese localisation for APAC.

Promoted to lead the Vendor Integrations portfolio. I ran three platforms handling terabytes of ad impressions, clicks, and attribution data daily across GroupM’s agency network, managing 12 vendor integrations and working with engineering and agency ops to maintain data quality at scale.

Joined post-GroupM acquisition to rebuild data ingestion infrastructure for a global media group. I owned the Vendor Integration Engine, maintaining connections with 12+ AdTech platforms, contributed to Proteus, an in-house campaign management platform, and eliminated several manual ops workflows to reduce risk and free the team to scale.

Part of the SEO Centre of Excellence, working across Ask.com and About.com. I tracked the impact of Google algorithm changes on search visibility and turned that analysis into concrete recommendations for engineering and editorial teams. I also prototyped a tool to detect and fix over-optimised content, early-stage R&D that fed into platform strategy.

Supported a company pivot into SEO-driven content, helping build sites that hosted 1.5M+ Q&A pairs generated from query log data. I worked on search quality and indexation, collaborating with engineering and analytics teams across a large-scale platform.

Year-long industrial placement during my degree. Built client sites, maintained Andalucia.com, and got my first taste of ad trafficking and online advertising.

This course introduced Claude’s core features and how to use them effectively at work. It covered the distinction between projects and skills, how connectors work and what data they can access, and how to use artifacts to share outputs with others. It also explained how to write effective prompts by setting the stage, defining the task, and specifying rules, as well as how to get better results when responses are too generic. Specialist tools like Claude Code and Research mode were also introduced.

This course covered the fundamentals of product discovery and how to build a data-driven process for understanding customer needs and deciding what to build. It explored how to incorporate AI at each stage of discovery, tactical approaches to gathering and analysing insight, and best practices for scaling discovery efforts across a product organisation.

This course introduced the Radical Product Thinking methodology, developed by Radhika Dutt, as an alternative to conventional approaches to product visioning. It focused on what makes a strong product vision statement, how to write a Radical Vision Statement, and how to use a clear vision to drive alignment across a team and organisation.

This course covered what it means to build effective digital experiences for internal audiences as part of broader digital transformation efforts. It explored how to analyse and optimise the way employees use software, how to reduce friction in business processes, and best practices for building and managing internal applications to drive measurable business outcomes.

This course explored how AI fits into the product manager role, covering practical use cases for applying AI tools across the product development lifecycle. It looked at best practices for building AI-powered features, how AI can accelerate product-led growth, and how to think about AI as a strategic tool rather than a disruption to existing ways of working.

This course covered the fundamentals of the product manager role through the lens of the Product Management Life Cycle: Discover, Validate, Build, Launch, Evaluate, and Iterate. It reinforced the shift away from shipping features as a measure of success towards delivering outcomes that matter to both customers and the business. It also covered common challenges in product management and the best practices for navigating each phase of the lifecycle.

This course deepened my understanding of product analytics methodology and how to build a data-driven approach to product decision-making. It introduced the Product Analytics Hierarchy of Needs as a framework for getting the most value from analytics data. It also covered practical use cases for analytics across the product lifecycle, how to use data to support higher-level business decisions, and how to build the organisational buy-in needed to make data-driven practices stick.

This course gave me a grounding in what it means to build and run a product-led organisation. It covered the shift from sales-led growth to a model where the product itself drives acquisition, activation, and retention. I also learned how to align teams around product-led principles, how to use data and in-app behaviour to improve user outcomes, and the cultural and structural changes needed to make it work in practice.

This course grounded me in the Scrum framework, its principles, and the values that underpin effective agile teamwork. It covered the product owner role in practice, including how to manage competing stakeholder needs, how to develop a clear product vision, and how to maintain and prioritise a product backlog. It also focused on understanding customers well enough to consistently choose the right increment of value to deliver next.