A complete application in a minute — tailored resume and cover letter, ready to send.
Insify, a fast-growing insurtech, is looking for a Data & Analytics analyst to own product area metrics across the Netherlands, Germany, and France. You will collaborate with product, growth, analysts and data engineers to shape measurements and roadmaps by turning data into actionable insights.
You will design experiments and analyze funnels across markets, explaining changes in conversion and retention, and ensuring numbers reconcile as we expand products and countries.
We sell a mix of insurance products to small businesses (SME's) in the Netherlands, Germany and France, and we are in the process of scaling into more markets.
Insurance is a numbers business, and most of those numbers are harder to trust than they look. Every product has its own lifecycle, its own risk reporting obligations and its own conversion funnel, multiplied by the nuances of every country we expand into. Most insurers live with that: a spreadsheet per question, a definition per team. We're building it differently: one metric layer that all teams argue from, so that a question gets answered once and the answer holds when we add the next product or country.
Insify is a high-growth scale-up backed by more than €40M from investors like Accel, Munich Re Ventures, and Formula 1 champion Nico Rosberg. In five years we've expanded from the Netherlands into France and Germany. Our mission: become the European leader in AI-powered SME insurance.
You would join the Data & Analytics team, the team that defines the numbers Insify runs on. You would own how a product area is measured: what we track, what it means, and the experiments that decide the roadmap.
Together with a group of analysts & data engineers, you would work with Product & Growth teams on how a small business finds us, buys, renews and claims, and on where that changes as we add products and countries. The team serves groups with genuinely different needs: our growth efforts demand fast signals, risk and financial reporting need numbers that still reconcile months later.
You're joining at an exciting inflection point: we have real traction, proven scale, and the decisions about where to invest next are being made on the numbers you would produce.
Not all of the above are hard requirements. If you're strong on most of these and eager to grow into the rest, we'd still love to hear from you.
Databricks and dbt, with SQL-based transformation. If you have not worked with all of it, that is fine. We care more about how you reason from data than about which tools you have used before.