Darum lohnt es sich
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Design and own marketing measurement methodologies, including incrementality testing, marketing mix modeling, multi-touch attribution, and experiment design Build statistical and machine learning models to evaluate channel effectiveness, forecast outcomes, and inform budget allocation Translate ambiguous business questions into rigorous analytical plans and deliver findings to both technical and non-technical stakeholders Requirements 5 or more years of experience in data science or quantitative analytics Strong track record in marketing measurement, experimentation, or causal inference Highly proficient in SQL and Python (or R) Comfortable working with large, messy, real-world datasets Hands‑on experience with incrementality and lift testing, marketing mix modeling, attribution xayajpt modeling, or A/B and experiment design Solid foundation in statistics and causal inference Able to work independently in an ambiguous environment Ability to scope own problems and communicate results persuasively to senior stakeholders
