Founding Data Scientist

About this role

This isn’t your regular job. Almedia is a place where those who want to push harder can accelerate their careers faster than anywhere else. We’re aiming to become Germany’s second bootstrapped unicorn. Almedia is already Europe’s #3 fastest-growing company in 2025 (FT1000). We are building the future of marketing by rewarding our community of over 95 million users for engaging with our advertisers’ products. We are offering a new way to acquire users for the biggest companies in the world.

FOUNDING DATA SCIENTIST We're looking for a Founding Data Scientist to work directly with leadership on zero-to-one measurement and growth problems. This is not a role for maintaining existing systems — it's for someone who can take an ambiguous, high-stakes question and build the data infrastructure to answer it reliably, then own what comes next. We value people who combine measurement rigour with builder instincts: someone equally comfortable designing a causal experiment and shipping the pipeline that operationalises its output.

WHAT YOU'LL DO - Own incrementality testing across marketing, product, and rewards — proving its value from hypothesis to business impact. - Build the data pipelines and measurement stack behind it, tying experiments to real shifts in user behaviour, monetisation, and multi-touch attribution. - Drive experimentation strategy across growth and product: design, run, and interpret tests with a sharp focus on causal validity — not just p-values.

- Own data products end-to-end: scoping, architecture, implementation, rollout. - Partner with C-level, engineering, and business stakeholders to turn measurement into live operational decisions. - Set the frameworks and practices the team can scale on. WHAT YOU NEED - Deep expertise applying causal inference and experimental design in practice, in real business contexts. - Hands-on experience building and operationalising attribution models in a real business context — not just running models, but making them useful.

- Proven zero-to-one experience: ambiguous problem, built the infrastructure, shipped something production-ready. - Proficiency in Python and SQL; GCP preferred; comfortable with modern data stack tools (dbt). - Experience with programmatic advertising, ML pricing, or mobile measurement — MMPs, probabilistic attribution, or similar is a strong plus. - Familiarity with AI and LLM tooling is a plus — whether that's integrating language models into data workflows, using AI-assisted analysis to move faster, or exploring how generative and predictive AI can sharpen measurement and personalisation at scale.