Consulting
Past engagements
The Ad Lab started as a consulting practice for the programmatic industry — taking the mystery out of data science and AI for companies across the supply chain. I'm not taking on engagements at present. This is what that work covered.
Types of work
- Data science and AI product strategy What to build and in what order — technical strategy, architectural approach and a delivery roadmap a team could actually be staffed against.
- Programmatic trading analysis Whether inventory was bought or sold at the right price for the goal. Detailed analysis of past campaigns, including what fraud and made-for-advertising sites were costing, and the carbon the activity emitted.
- Programmatic strategy Supply paths and pricing for a given piece of inventory — a detailed buying and selling strategy using custom bidding, supply path optimisation, or both.
- Model remediation Why a model was underperforming and what to change — new approaches to existing modelling problems, plus management of the work to put them in place.
- Hiring data science and data engineering staff Finding qualified candidates for a specific problem: writing the role, sourcing candidates, and assessing them properly.
- Diligence for investment and M&A The real state of a target's data science capability and architecture — what they had, what they claimed, and the distance between the two.
Fractional Chief Data Scientist and CTO
- Maturity assessment Where the data science function actually stands, using a lightweight proprietary assessment model.
- Visibility for leadership Scrum or Kanban put in place so the executive team and the data science team could see the same picture of the work.
- Partnership and business development Leading data, analytics and technology partnership discussions where the technical detail decides the deal.
- Day-to-day management Running data science, data engineering and technical teams through a stretch where they needed a senior hand.
We used Ken for multiple engagements throughout a variety of the stages of Veritonic. In the early days, he was an essential advisor on a variety of data science projects and played a pivotal role in helping us scale our tech team. As we grew, Ken helped us get organized, scale, and properly manage our growing data science team. Each time Ken stepped into our startup chaos and brought a great sense of calm, experience, and the ability to help us get the important things done.
If you were hoping to hire me
My time goes to a full-time role and to the projects on this site, so I'm not available for engagements at the moment. If you have a problem in this territory anyway, email me — worst case I'll point you at someone better placed to help.