Lead Data Scientist

Every day our platform runs thousands of prompts across the major AI platforms and records what comes back: which brands get mentioned, which sources get cited, how they are described and how that changes over time. We have been collecting this long enough that it is now one of the richest datasets on AI search anywhere.

Today the platform tells customers where they stand. The question every marketer actually wants answered is why an LLM recommends one brand over another, and what they should do about it. Your job is to answer it, and to take the platform from insight to action.

• We've just raised $1.2m, led by SFC Capital, to build specialist AI agents trained on the GEO playbook from a year of client work

• In our first year we captured and analysed over 10 million AI answers, and that number is growing fast

• You'll be the first data scientist, so you'll set how we turn that data into insight rather than inherit someone else's approach

• Meaningful equity, alongside a salary of £80,000 to £100,000

• AI search is one of the fastest-moving areas in marketing, and what you find will shape the product and every client recommendation we make

Obsero is one of the UK's leading AI search startups. We track how brands are cited and recommended across ChatGPT, Gemini, Perplexity, Google AI Mode and Claude, so marketing teams can see where they stand in AI answers and what to do about it. Buyers are increasingly asking AI rather than searching, and we help the brands that want to be in those answers get there.

You will build the GEO playbook from the data, the recommendation engine that puts it in front of customers, and the models that tell them which actions will make the biggest difference. Along the way you will find new ways to look at the data that nobody else in the market can.

This is a lead role reporting to a founder, and you will own the problem end to end, from a clean, trusted dataset through to models running in the product. Our lead data engineer owns how the data is captured, cleaned and stored, so your time goes on what it means rather than on fixing it.

• The GEO playbook. Using our historic prompt data to build a deep understanding of what drives LLMs to recommend one brand over another, separating the factors in content, citations, sources and brand presence that genuinely move visibility from the ones that only look like they do, and turning it into a playbook our consultants and customers act on and that stays current as the AI platforms change

• The recommendation engine. Productising Obsero's GEO recommendation engine in the platform, moving customers from AI search insight to action and in turn growth, working with product and engineering so recommendations land in a form customers trust and use, and measuring whether they work so the results feed back into the engine

• Predictive models. Models that predict the likely impact of different actions for each customer, so we can prioritise the ones that will make the biggest difference and customers know what to do first

• New insight. Exploring new ways to transform and analyse the data to generate unique and valuable insight, prototyping quickly, sharing what you find and turning the best ideas into features

This is not a reporting or dashboarding role. We want someone who asks better questions of the data than we do, and builds the models and products that answer them.

• Several years of hands‑on data science experience, with a track record of taking models from analysis into production

• Strong in Python and SQL, and comfortable building the analysis and feature pipelines your models need

• Experience in statistical modelling, causal inference or experimentation, and the judgement…