Applied Scientist

SE Ranking, an all-in-one SEO and digital marketing platform, is looking for a Lead Applied Scientist to reverse-engineer how AI search and generative platforms (ChatGPT, Gemini, Perplexity, AI Overviews) recommend and describe brands - and to build the measurement layer that proves what AI visibility is actually worth to a business.

This is a founding-level role for a new discipline: AI Search Optimization and Brand Intelligence for Generative AI. This is not classic SEO, and it is not classic data science. You will be the technical owner of the research agenda - from hypothesis to experiment to insight to shipped product capability - and you will work alongside a small team (one ML Engineer today, a second one you will help hire), while staying deeply hands-on yourself.

Why this role is different

• You get proprietary data most researchers can only dream about: SE Ranking's SERP, backlink, content, audit, GA and GSC datasets, plus Planable's social media data - combined with systematically sampled AI-generated responses
• Your output is not only product features. It's the GEO best practice the industry will end up using - with the opportunity to represent that work at conferences and in company research, if that's something you'd enjoy
• The discipline is barely a few years old. Nobody is "the expert" yet - the first rigorous answers will come from someone with your access to data

How the role splits

This is primarily a hands-on technical role with some team leadership on top - you'll stay deeply hands-on in research and modelling, while also directing a small team's day-to-day work: setting technical direction, running 1:1s, unblocking people, and contributing to hiring decisions:

• ~45% hands-on research and modelling - you design and run experiments yourself
• ~45% technical and project leadership - hypothesis prioritisation, decomposition, methodology review
• ~10% people management - directing a small team's day-to-day (1-2 people): setting technical direction, running 1:1s, unblocking people

What you'll do - first 90 days

• Partner with our SEO/GEO specialists and selected engineers to set up a repeatable experiment pipeline: hypothesis → data scope → design → run → insight → decision
• Run the first 3-4 experiments and, with Product, define candidate features that would give our customers a real AI-visibility practice
• Design sampling methods to systematically collect and analyse AI responses across topics, intents and regions - with explicit handling of variance, bias and representativeness