Data Scientist – MarTech (Measurement & Optimization)

Google Chrome Microsoft Edge Apple Safari Mozilla Firefox Data Scientist – MarTech (Measurement & Optimization)Full-timeCompany DescriptionGlovo is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience—fast, easy, and to your door. We operate in around 65 countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index.Job DescriptionThe MarTech Data Science team drives performance marketing efficiency through advanced measurement, optimization, and scalable modeling.We operate in a highly complex and ambiguous environment where:Ground truth is often unobservable (incrementality vs attribution)Clean experimentation is not always feasibleDecisions must be made under uncertainty with imperfect dataWe build solutions for budget allocation, incrementality measurement, and bidding, enabling the business to invest each euro where it generates the highest impact. YOUR MISSIONWe are looking for a Data Scientist to own models and features end-to-end within larger MarTech initiatives, and contribute to the team's measurement and optimization solutions. Operating at a global level, you will design solutions that serve the entire Delivery Hero portfolio, including brands like Glovo, Talabat, and PedidosYa.   You will work autonomously on well-defined problems and collaborate closely with senior team members on more ambiguous ones.This role requires solid foundations in causal inference and modeling, combined with the ability to communicate clearly with technical and non-technical stakeholders and translate marketing problems into reliable, production-grade solutions. THE JOURNEYOwn features and components end-to-end within MarTech measurement & optimizationTake ownership of models and features inside larger initiatives, from data exploration to production deploymentContribute to defining success metrics and modeling approaches, with senior guidance on more ambiguous problem framingsBalance methodological rigor with business constraints and timelines Contribute to decision frameworks under ambiguityHelp translate marketing questions into structured, model-driven analysesOperate in environments where experimentation is limited or infeasible, applying established methods across MMM, experiments, and observational analysisMake and document assumptions explicitly, and flag their impact on decisions Support decision-making under uncertaintyProvide clear analyses despite imperfect measurement, articulating trade-offs and limitationsIdentify conflicting signals (e.g., attribution vs incrementality vs MMM) and discuss them with senior team membersEnsure outputs are actionable and aligned with real business constraints (budget caps, pacing, channel dependencies) Apply methodological rigor and contribute to validationContribute to and apply frameworks across MMM, incrementality testing (geo experiments, synthetic control), bidding, and/or LTVApply validation strategies in the absence of ground truth (cross-method validation, backtesting, sensitivity analysis)Follow team standards for statistical rigor, interpretability, and reproducibilityParticipate in knowledge sharing within the chapter and team Communicate effectively with stakeholdersTranslate modeling outputs into clear narratives for non-technical stakeholdersCommunicate with squad-level stakeholders, adapting abstraction level appropriatelyAddress questions on model outputs with appropriate context and honesty about limitations Build production-grade systemsDevelop reliable, maintainable solutions with good standards in testing, monitoring, documentation, and reproducibilityWork closely with Engineering and Product to deploy and improve systemsEnsure long-term usability of models as decision products, not just analysesQualificationsStatistical, Causal & Predictive FoundationsSolid foundation...