Data Analyst

We're looking for a Senior Data Analyst who's equally happy designing an experiment, arguing about what a metric actually means or modelling data. You'll own the analysis behind how we decide things — which tests are worth running in collaboration with our stakeholders, what the results actually say, and what we should do next — or help build AI Analyst, our internal MCP that lets anyone ask the data a question without filing a ticket. Your work will shape the numbers the company steers by, from the product North Star to the leading indicators that tell us where revenue is heading before it gets there. You'll work across product, marketing, R&D and revenue, alongside a small, senior data team and our engineers, using SQL, dbt, Looker and Python. If you like broad problems, short paths to impact, and having your recommendation actually change what happens — you'll feel right at home.

🚀 What you'll do

• Drive high-impact projects end to end — from a vague business question to a shipped outcome. We'll agree the why and the what together; the how is yours.
• Design and assess experiments — judge whether an A/B test is viable in the first place, design it properly when it is, and build a credible pre/post or quasi-experimental read when it isn't
• Analyse experiments honestly and say what they mean — including the ones that didn't work, and the ones where the data can't carry the conclusion someone wants
• Make recommendations, not just dashboards — a big part of this role is landing a point of view: what we should do, why, and what you'd need to see to change your mind
• Define the metrics the company steers by — and how are they impacted by the different levers we have to achieve our goals
• Build the datasets and models the rest of us rely on — ETL/ELT transformations, curated datasets per business use case, and our migration to dbt
• Help build AI Analyst, our internal MCP, so stakeholders can self-serve answers — and partner closely with product, marketing, R&D and engineering, keeping expectations managed and flagging delays early with a reason and a new date

👏 We're looking for someone who has

• Solid senior-level experience as a data analyst in SaaS — you know NDR, expansion, contraction and MRR as things you've modelled, not terms you've heard
• Real experimentation depth — you've designed, sized and analysed A/B tests, you know when a clean test isn't possible and what you'd do instead, and you're comfortable being the person who says a result isn't significant
• A habit of ending with a recommendation — you're analytical and opinionated, you tell people what you think they should do based on evidence, and you're clear about how confident you are
• Expert SQL, Python for the work SQL can't do, and comfort in Looker (or a close equivalent) for getting insight in front of people
• Strong data modelling and analytics engineering — you build the layer everyone else relies on rather than just querying it, with real dbt mileage
• A genuine appetite for AI — you're already using it in your workflow and curious about what it changes for analytics
• Generalist range and real autonomy — you move between product, marketing, R&D and revenue questions, drive your own projects, know who to ask when you're stuck, and don't stall when priorities shift in a lean remote team

➕ Bonus points, if you have

• Data science experience — building ML models and getting them into production
• Experience at principal or staff level; we're open to those levels for the right person

📍 Where you'll work

Remote, from anywhere within CET ±1 — including the EU, UK, Ukraine and South Africa. Hours are flexible, with a general expectation that you're available and responsive across CET 9–5. Flexibility works both ways.

🎁 What we offer

• 22 days of paid time off, plus your local national holidays
• Flexible work hours and a culture that trusts you to manage your time
• Private medical insurance or a medical allowance (depending on your location)
• Extended paid sick leave so you can fully recover without worry
• Career map with growth opportunities
• A quarterly learning budget for courses, books, or anything that helps you grow professionally
• A quarterly wellbeing budget you can use for sport, therapy, or even a good novel
• Best hardware for your work (team Apple)
• An award-winning product loved by thousands of customers worldwide
• A transparent, flexible culture with people at the core of everything we do
• Events that are actually fun