Senior Data Scientist, Marketing

About the role

This role is centered on constructing a rigorous scientific measurement layer that connects attribution, marketing mix modelling, and incrementality testing into a single automated framework. The hire will own the end to end design of geo tests and incrementality studies, using experimentation as the primary instrument to establish what truly drives growth. You will translate ambiguous marketing questions into clear causal inference problems and turn the findings into production models that directly influence CLV, CAC, and revenue decisions. The position requires building durable measurement infrastructure and models that the Growth Marketing, CRM, and MarTech teams rely on daily to scale efficiently in competitive markets. You will communicate results persuasively to both technical and non technical stakeholders, driving adoption of data backed recommendations across Marketing. The role involves bringing AI native analytics workflows, including agentic data exploration and LLM assisted causal analysis, into the team's everyday practice. You will own the standard that the marketing organisation uses for budget, channel mix, and retention decisions through advanced steering mechanisms.

Key facts

What you'll do

• Design and run experiments as a discipline, overseeing the full cycle from test design through analysis to business decisions based on geo tests and incrementality studies.
• Advance steering mechanisms using regression, Bayesian inference, and causal inference to convert open ended budget questions into clear decision frameworks that increase CLV and reduce CAC.
• Own and evolve the marketing measurement stack, including attribution, MMM, incrementality testing, and brand tracking, establishing the standards used by the entire marketing organisation.
• Build production grade models such as CLV and demand forecasting that feed live decisions on budget allocation and channel mix rather than one off analyses.
• Communicate analytical results persuasively to both technical and non technical audiences, ensuring that recommendations are understood and implemented across Marketing.
• Integrate AI native analytics workflows, leveraging agentic data exploration and LLM assisted causal analysis to improve speed and rigor of insights.
• Translate business problems into analytical approaches, selecting appropriate methods and rigorously evaluating their performance in production environments.
• Partner closely with Growth Marketing, CRM, and MarTech teams to embed measurement into core workflows and ensure models are used at scale.
• Define and track key success metrics, documenting assumptions, limitations, and insights to maintain transparency and reproducibility.
• Continuously explore emerging methods and tools, proposing improvements to the measurement stack that keep pace with evolving channel landscapes.

Must have

• 5+ years in data science or analytics, ideally with exposure to marketing or growth contexts and a track record of delivering measurable impact.
• Strong statistical and causal inference foundation including regression, Bayesian methods, and especially incrementality testing, with the ability to design a test from scratch.
• You can pick the unit of randomisation, reason about power and minimum detectable effect, and defend the runtime with more than intuition when designing experiments.
• Deep understanding of marketing attribution, not just channel mechanics, including what a multi touch model can and cannot tell you and how to triangulate attribution against incrementality reads.
• Advanced SQL and Python skills, comfortable working with sparse, high dimensional advertising data and transforming it into reliable inputs for modelling.
• Hands on experience with AI driven workflows, such as prototyping with LLMs, automating pipelines, or using AI powered IDEs to accelerate delivery of analytical solutions.
• Proactive and outcome driven mindset, someone who picks up a project and drives it fully from data pipeline to business recommendation without needing constant direction.
• Strong written and verbal communication skills to explain complex analytical concepts to both technical and non technical stakeholders.
• Ability to work independently and collaboratively in a fast paced, international environment where priorities evolve quickly.
• Willingness to iterate based on stakeholder feedback and align measurement practices with business objectives across regions.

Nice to have

• Experience with Marketing Mix Modelling, where formal MMM experience is a bonus but understanding the regression underneath is what truly matters.
• Machine learning experience in areas such as classification, clustering, forecasting, and CLV prediction, which is a strong plus but not a blocker.
• Proficiency with dbt for data modelling and familiarity with BI tools such as Looker, enhancing the reliability and accessibility of insights.

Practical notes

This is a full time position based in Berlin with no required travel. The role is not eligible for visa sponsorship at this time. Applications will be reviewed on a rolling basis until the position is filled, so early submission is encouraged.