Senior Data Scientist, Dynamic Promo - Quick Commerce

Google Chrome Microsoft Edge Apple Safari Mozilla Firefox Senior Data Scientist, Dynamic Promo - Quick CommerceFull-timeCompany DescriptionAs 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, powered by tech, designed by people. As one of Europe’s largest tech platforms, 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. We push hard, learn quickly and stay human along the way. It’s this wonderful mix of high performance and real community that makes Delivery Hero a place where ambition and belonging grow side by side. If you’re curious, collaborative and ready to dive deep into meaningful work, you’ll fit right in.Job DescriptionWe are on the lookout for a Senior Data Scientist, Dynamic Promo, to join Quick Commerce on our journey to always deliver amazing experiences.Be part of redefining how customers experience quick commerce. You’ll help build technology that scales our non-food offerings, reaching new market segments and driving revenue growth. By innovating within our Quick Commerce Team, you’ll make Delivery Hero the go-to platform for a broad range of products, helping us grow faster and deliver more value to customers around the world.This is a role for a proactive individual who has already worked on causal inference, time series problems at scale, as well as user-facing personalization and is hungry to lead initiatives independently. You will drive hypotheses, run A/B tests on customer-facing uplift models, and bring robust causal and time-series architectures into production with real business impact. If you’re a strong coder with a hacker mentality and thrive in high-scale applied ML and econometric problems, we’d love to talk.Design, experiment, and deploy classical ML and uplift models (including personalisation) to measurably improve affordability perception and user experience at global scale.Independently lead end-to-end data science initiatives, from technical design and implementation to effective communication with business stakeholders.Drive experimentation: formulate hypotheses, analyze A/B tests, and turn insights into production-ready solutions for better targeting and incentive deployment.Apply advanced time series and causal inference techniques to model and forecast the supply and demand of incentives.Leverage live user signals and context to make affordability interventions more adaptive and dynamic.Collaborate closely with MLEs and Engineers to ensure solutions are scalable, reliable, and fast in production.Contribute to the long-term vision of affordability intelligence and personalisation at QC, while delivering short-term wins that unlock measurable business impact.Mentor and inspire peers, raising the quality bar for Data Science in causal inference and personalization across the tribe.  Qualifications5+ years of industry experience applying Data Science and Machine Learning in production, ideally in large-scale consumer-facing applications.Expertise in causal inference and uplift modeling for user targeting and intervention strategies, alongside time series analysis.Strong statistical foundations and ability to distinguish signal from noise in large-scale experimentation and A/B testing.Excellent engineering skills: write clean, maintainable Python code; experience bringing ML models into production with best practices for observability and monitoring.Proven ability to lead independently and work cross-functionally with engineers and product stakeholders, translating business problems into DS solutions.A proactive hacker mentality: pragmatic, hands-on, and comfortable iterating fast to get solutions live.Nice to have:Experience scaling personalization and causal systems across multiple markets and heterogeneous platforms.Familiarity with cloud platforms...