Senior Data Scientist – MarTech (Measurement & Optimization) at DeliveryHero

The 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 feasible • Decisions must be made under uncertainty with imperfect data We build solutions for budget allocation, incrementality measurement, and bidding, enabling the business to invest each euro where it generates the highest impact.    YOUR MISSION We are looking for a Senior Data Scientist to own end-to-end initiatives, shape problem definitions in ambiguous contexts, and drive decision-making through rigorous models. Operating at a global level, you will design solutions that serve the entire Delivery Hero portfolio, including brands like Glovo, Talabat, and PedidosYa. This role requires strong causal inference and modeling expertise, combined with the ability to influence stakeholders and translate complex marketing problems into robust, production-grade solutions.   THE JOURNEY Own end-to-end marketing measurement & optimization solutions • Lead ambiguous, high-impact problem spaces from problem framing to production • Define success metrics and modeling approaches when requirements are not clearly specified • Balance methodological rigor with business constraints and timelines   Translate ambiguity into decision frameworks • Convert vague marketing questions into structured, model-driven decision systems • Operate in environments where experimentation is limited or infeasible, and triangulate between MMM, experiments, and observational methods • Make and justify assumptions explicitly, and assess their impact on decisions   Drive decision-making under uncertainty • Provide clear recommendations despite imperfect measurement, articulating trade-offs and confidence levels • Navigate conflicting signals (e.g., attribution vs incrementality vs MMM) • Ensure outputs are actionable and aligned with real business constraints (budget caps, pacing, channel dependencies)   Lead methodological design, validation, knowledge transfer • Design and evolve frameworks across MMM, incrementality testing (geo experiments, synthetic control), bidding, and LTV • Establish robust validation strategies in the absence of ground truth (cross-method validation, backtesting, sensitivity analysis) • Set standards for statistical rigor, interpretability, and reproducibility • Drive internal & external knowledge sharing across Delivery Hero and industry. Drive adoption and stakeholder alignment • Translate complex modeling outputs into clear narratives for non-technical stakeholders • Communicate with stakeholders ranging from squad ICs to tribe leadership, adapting abstraction level appropriately • Handle pushback on model outputs and build trust in methodologies over time   Build production-grade systems • Develop reliable, maintainable solutions with high standards in testing, monitoring, documentation, and reproducibility • Work closely with Engineering and Product to deploy, scale, and continuously improve systems • Ensure long-term usability of models as decision products, not just analyses