Data Science Manager
Summary
Manager role at a PE-backed data & AI consulting firm in London (hybrid): you first train a new cohort of engineers in data, AI and modern systems, then stay hands-on, deploying with them into end-client environments and owning technical delivery as a consultant.
Data Science & AI Manager
PE-Backed Data & AI Consulting Firm
Build. Teach. Deploy
London, Hybrid
£70k - £90k
We are partnered with a PE Backed global Data & AI Consulting firm looking to completely re-imagine how they train and deploy their talent pools.
With aspirations to reach Unicorn status within 3 years, you'll be joining a rocket ship already successfully disrupting the data and AI consulting market.
You’ll start by helping shape a new generation of engineers — people learning how to build properly across data, AI, and modern systems, teaching what actually works in production, based on your own commercial experience.
Then your role evolves.
As those engineers move into client environments, you go with them — not as a trainer, but as a consultant. You’ll stay hands-on, work directly with end clients, and take ownership of delivery. You’ll lead from the front, guiding both the technical direction and the people you’ve helped develop.
It’s a deliberate blend: build capability, then deploy it.
The people who tend to lean into this are engineers with a strong foundation in AI, data, or backend systems who’ve already operated in consulting or client-facing environments. They’ve built real systems, understand the gap between theory and production, and naturally find themselves mentoring others — whether that’s through workshops, internal training, or just being the person others go to when things get complex.
You don’t need to have been a full-time instructor. But you do need to care about how things are built, how they’re taught, and how they actually land in the real world.
What makes this different is that you’re not stepping away from engineering to teach, and you’re not stuck in delivery without broader impact. You get both. You help shape how people are trained, and then you see that training hold up — or break — in real client environments, and refine it accordingly.
If you’re starting to enjoy the mentoring side of engineering, but don’t want to lose the technical edge or the pace of real-world delivery, this is a pretty rare way to do both without compromise.
Skills & Experience Required
- Educated to degree level in a STEM subject; Mathematics, Statistics, Engineering, Chemistry, Physics, Computer Science, Machine Learning
- A commercial background in building and delivering data science and AI solutions end to end
- Ability to lead teach and deploy teams of engineers, data scientists and AI engineers onsite with end clients - ideally with some formal experience in the training space
- Strong consulting skills, ability to work directly with end customers on shaping data and AI solutions, overseeing delivery from deployed teams
