About the Role
Who we areLemrock builds the infrastructure of agentic commerce.Tomorrow, consumers won't just buy on e-commerce websites. They will discover, compare and purchase directly inside conversational AI interfaces like ChatGPT, Perplexity, and a growing long tail of specialized AI assistants.For brands, this is a major shift: if they are not present in these environments, they become invisible.Our mission: enable any brand to exist, sell and distribute in this new channel.We raised a €7M seed round (the first in Europe on this market), with Jean-Baptiste Rudelle, founder of Criteo, on our board, and the Bpifrance DeepTech label.Today, Lemrock is already:100M+ conversations per month150+ brand clientsa $100B market structuring at high speedThe roleWe are accelerating. The product works, clients renew, the market is taking shape. Every day, shoppers talk to AI agents before they buy, and conversion has been at the heart of how we build the product from day one. We now want to go further and faster, with someone fully dedicated to understanding what turns a conversation into a purchase, and to proving it with data.As our freelance Data Scientist, full-time, you will dig into everything we have and tell us what drives conversion, what to change in the product next, and how to prove it. You will build on the work already done, challenge it, and find the levers we have not seen yet. You will work directly with the founders and the product and engineering teams.Understand what drives conversionExplore every data source we have: natural-language conversations, behavioural events, conversion tracking, product and advertiser metadataTurn raw conversations into usable signals (intents, categories, features) that you define and buildLink what our agents say (answers, recommendations, tone) to what users do next, and turn it into concrete improvements for the agent teamFind the next levers that move purchases, and size the impact of each oneExperimentTurn your findings into prioritised hypotheses the product team can act onDesign the A/B tests that validate them, then read the resultsThe engineering team implements the variants: you do not write production codeStrengthen what we measureSpot the remaining blind spots in what we measure and specify the events and properties we are missing, for the engineering team to implementProfileMust-have4+ years of hands-on data science or analytics, with analyses that changed a product or business decision.Advanced SQL and Python for dataStrong statistics and experimentation: A/B test design, causal reasoning, and the judgment to separate real effects from noise, selection bias and measurement artifacts, and to know when the data is too thin to concludeAutonomous: you find the right questions in an open problemAI-forward: you use AI tools (Claude, Cursor, agents) dailyFluent French and professional EnglishAvailable now, full-timeA plusNLP on real text data: classification, clustering, LLM-based labellingE-commerce or retail experienceConversion, CRO or funnel analyticsBigQuery, PostHogAdtech or performance-marketing measurement (attribution, ROAS)Familiarity with ranking, recommendations or search relevanceStartup experienceNo school requirement.The missionFreelance, full-time, starting ASAP1 month minimum, around 3 mont