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Senior Data Scientist, Marketing (d/f/m)
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Job Description
Our story: Every year millions of people are either filing their taxes in fear or giving up on their tax refund altogether. We're working on fixing that. Our intuitive app enables anyone, regardless of education or background, to file their taxes with newfound confidence.
Spread across Germany, Spain and the UK, the team at Taxfix Group with its brands Taxfix, Steuerbot and TaxScouts, is a compassionate group of solution-finders. We speak our minds openly, and with over 400 professionals, including tax experts, developers, and IT security experts, we're rich in ideas and voices.
The group has facilitated more than 3. 5 billion euros in tax refunds for its customers since its founding in 2016. Why this role, why now? Our data infrastructure and marketing foundations are already in place.
We run a large marketing budget across competitive digital channels and our stakeholders are data-driven - they run experiments and dig into data themselves. What's missing is the rigorous scientific layer that connects attribution, MMM and incrementality testing into one coherent, automated measurement framework.
You will own that build. Your challenge: Join our Marketing Analytics team as a Senior Data Scientist, where your mission is to build the measurement and modeling capability that decides how we grow.
You will own how Taxfix measures marketing causally and turn that into production models that directly shape CLV, CAC, and revenue. Your output is durable measurement infrastructure and models that the Growth Marketing, CRM, and MarTech teams rely on every day to scale efficiently in competitive markets.
Your responsibilities and decisions: Design and run experiments as a discipline. Geo tests and incrementality studies are your primary instrument for establishing what actually drives growth. You’ll focus on a full cycle from choosing the design to reading the result and turning it into a spend decision.
Advance our steering mechanisms (regression, Bayesian inference, causal inf
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