Lead Applied Scientist – AI Search, Brand Intelligence

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🔥 1 minute ago

🇪🇺 Europe – Remote

⏰ Full Time

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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SE Ranking

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2012

💼 Consulting

📣 Marketing

🛍️ eCommerce

Consulting • Marketing • eCommerce

SE Ranking is an all-in-one SEO platform designed to enhance online visibility and digital marketing strategies for agencies and businesses of all sizes. Established in 2013, it provides a wide range of tools including rank tracking, website audits, backlink checks, and comprehensive keyword research, all powered by advanced AI technology. Trusted by over 40,000 businesses globally, SE Ranking aims to make SEO management accessible and effective, ensuring users can optimize their strategies based on insightful data and analytics.

📋 Description

• Reverse-engineer how AI search and generative platforms recommend and describe brands • Build the measurement layer for the business value of AI visibility • Own the research agenda from hypothesis through experiment, insight, and shipped product capability • Design and run experiments and establish a repeatable experiment pipeline • Set technical direction, prioritize hypotheses, review methodology, and direct a small team's day-to-day work • Run the first 3-4 experiments and define candidate product features with Product • Design sampling methods for AI responses across topics, intents, and regions, handling variance, bias, and representativeness • Establish evaluation frameworks for LLM outputs, prompts, and model behaviour • Apply LLMs via batch APIs as feature extractors and judges, including prompt evaluation, cost-aware batch inference, and agentic/tool-using pipelines • Own model evaluation and validation standards • Develop predictive, ranking, classification, clustering, and representation-learning models • Analyse SERP, backlink, content, audit, GA, and GSC data in ClickHouse or similar columnar OLAP at hundreds-of-millions-of-rows scale • Source and generate hypotheses, maintain a prioritized backlog, and manage the execution cycle • Mentor ML Engineers and participate in hiring • Turn findings into product features, published research, conference talks, and GEO best practices with Product, Engineering, Marketing, and Leadership

🎯 Requirements

• 5-6+ years in Data Science or Applied Science • Track record of taking ambiguous research problems from hypothesis to a shipped decision • Deep, hands-on expertise in ranking and information retrieval, including learning to rank, NDCG/precision@K, LambdaRank/LambdaMART • Strong, current GenAI/LLM expertise, including prompting and evaluating commercial APIs and open-weight models • Experience with LLM-as-judge or agent evaluation • Understanding of how sampling, context, and model behaviour affect model outputs about brands • Rigorous model evaluation and validation, including leakage detection, temporal/out-of-time validation, and business-outcome metrics • Ability and willingness to direct a small team's day-to-day work (1-2 people) • Solid English (B2+) • Gradient boosting with LightGBM/CatBoost is nice to have • Embeddings and representation learning with sentence-transformers/faiss is nice to have • Ability to analyse large-scale data directly, such as ClickHouse, is nice to have • Interest in SEO/search domain is nice to have • Familiarity with AI-search measurement concepts is nice to have • MLflow or similar experiment tracking experience is nice to have • Publications or talks are nice to have

🏖️ Benefits

• Direct, ticket-free access to SE Ranking's SERP, backlinks, content, audits, GA/GSC datasets, plus Planable's social media data • Dedicated data/analytics engineering support • Dedicated LLM API budget for systematic response sampling (OpenAI, Google, Anthropic, Perplexity) • Opportunity to publish conference talks, research, and company best practice • Authority to launch experiments without asking for permission first