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Who we are Lemrock 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 month 150+ brand clients a $100B market structuring at high speed The role We are accelerating. The product works, clients renew, the market is taking shape. Every day, shoppers talk to AI agents before they buy, and performance has been at the heart of how we build the product from day one. We now want to go further and faster: understand precisely what makes our campaigns and recommendations perform, and apply it to the product continuously. As our freelance Analytics Engineer, full-time, you will dig into our data to find what drives performance, then turn your findings into changes in the product. You will work directly with the founders and the product and engineering teams. Understand what drives performance Explore every data source we have: conversations, web and behavioural events, campaign performance, product and advertiser metadata Find what drives performance and size the impact of each lever Measure every change with A/B tests, and feed the results back into the next analysis Turn findings into changes Apply what you find to the product yourself, with Claude Code: which products we prioritise, who we show them to, how we present them Write and maintain the Claude Code skills that make these updates repeatable, reviewed by the engineering team Build data that lasts Model our data in BigQuery so every analysis can be rerun, not rebuilt Build the semantic layer and the shared metrics the whole team relies on, readable by our agents and Claude Code skills as well as by people Test and document your models so the team can trust them Specify the events and properties we are missing, for the engineering team to implement After 3 months Our core performance metrics are modelled, tested and exposed in the semantic layer Campaign performance has measurably improved: you ship changes every week, each one measured by A/B tests The update loop runs through Claude Code skills the team can rerun Profile Must-have 3+ years as an Analytics Engineer, Data Analyst or Data Engineer, with real analysis work Advanced SQL, solid Python for analysis Dimensional modelling on BigQuery (dbt or equivalent), with Git, pull requests and code review You have built a semantic layer and BI on top of it (Lightdash, Looker or similar) Solid statistics: A/B tests, ideally causal inference. You have turned an analysis into a product change and measured what it moved Autonomous: you find the right questions in an open problem, turn your findings into clear recommendations, and challenge the requests you get You use Claude Code or similar tools every day, and have already built your own workflows with them A plus B2C, e-commerce, marketplace or advertising experience Ads measurement: attribution, CTR, ROAS Growth, conversion, CRO or funnel work You have put rerunnable data pipelines in production Product analytics: PostHog, Amplitude, Mixpanel Startup experience The mission Freelance, full-time, starting within 2 to 3 weeks 3 months, renewable For the right person, the mission can turn into a permanent role Fluent French and professional English Our stack: BigQuery, dbt, Lightdash, PostHog, Python Process: a 30-minute technical fit, then a data exercise on a real dataset (2 to 3 hours on your side, then a 20-minute debrief of your insights). Decision within the week. Why join

Analytics Engineer (Contract)

Don't apply unprepared

Analytics Engineer (Contract)

Don't apply unprepared