Bodhi
Senior Data Scientist
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Data Science Lead
London or Amsterdam
Up to £75K
Hybrid working
This is a rare opportunity to sit at the analytical heart of something genuinely new — a proprietary measurement platform being built by the consulting division of the world's largest independent creative network.
The platform — developed in research collaboration with one of the world's most prestigious business schools and underpinned by over a billion data points — quantifies the commercial return on cultural influence for brands. It's a peer-validated methodology that answers a question the marketing industry has never been able to answer before: what is culture actually worth, commercially?
Clients already deploying this include some of the most recognised brand names on the planet — spanning consumer goods, luxury, sport, technology, and financial services.
You'll be the analytical and technical engine that turns that methodology into working data products — models, scorecards, and insight tools — built for and delivered directly to global brand teams.
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The Role
Working directly with the Head of Effectiveness Solutions and alongside the Head of AI & Product and Global Delivery Lead, you'll own the science behind the product. That means framing analytical problems correctly, choosing appropriate methods, building models that are trustworthy rather than just technically impressive, and standing behind your outputs in a client room.
This isn't a back-office research role. RoCP products are delivered to brand teams at global organisations — which means you'll be explaining methodology in plain language, fielding tough questions, and pushing back confidently when a question rests on a misreading of the data.
AI-assisted development is a core part of the workflow here, not an afterthought. You'll be expected to ship working models and pipelines using these tools, and to have genuine opinions about when they accelerate and when they don't.
Essential skills required
- Statistical foundation: Strong grounding in statistics and applied modelling — inference, regression, classification, clustering, and model validation. You know how to frame a problem, choose an appropriate method, and interrogate whether the output is signal or artefact.
- Stakeholder confidence: You can hold a room, translate a model into plain language, and push back politely when a question is based on a misreading of the data. You've done this with senior stakeholders and client teams before.
- Engineering self-sufficiency: 3+ years working with data in Python and SQL. You can pull from APIs, clean and structure messy real-world datasets, and stand up a working pipeline end-to-end without hand-holding.
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Desirable skills
- Demonstrable use of AI coding tools (e.g., Claude Code, Cursor, GitHub Copilot, or equivalent) to ship working code — and real opinions about the limits of agentic development.
- Experience with dbt, dimensional modelling, or building analytical data layers.
- Familiarity with marketing data ecosystems — ad platform APIs, brand tracking, audience data, or attribution modelling.
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