Staff Data Scientist - AdTech Ranking | Staff Data Scientist - AdTech Ranking
Delivery Hero SE
Job Summary
As a Staff Data Scientist on the AdTech Ranking Team at Delivery Hero, you will be a visionary leader driving transformative innovation in AI-powered ranking and bidding systems. Based in Berlin, you will lead the creation of advanced machine learning models that redefine auction dynamics and maximize advertiser ROI across a global platform operating in over 50 countries. Your day-to-day involves designing and deploying mission-critical, ultra-low-latency real-time decision systems while balancing complex multi-objective problems like revenue, engagement, and fairness. This role is unique as it offers the opportunity to shape the long-term technical strategy for one of Europe’s largest tech platforms, influencing the roadmaps of multiple engineering and product teams. You will act as a thought leader, mentoring senior staff and applying cutting-edge research in reinforcement learning and causal inference to deliver multi-million-euro business outcomes. The position is ideal for experts who want to solve intractable problems at a massive scale within a fast-paced, MDAX-listed ecosystem.
Required Skills
Education
Not specified
Experience
- Professional experience designing, building, and deploying multiple generations of large-scale AI systems with measurable business outcomes
- 2+ years of experience driving organizational-wide technical strategy for Data Science and Machine Learning
- Leadership experience mentoring Staff and Senior Staff engineers or scientists
- Proven track record in optimizing CPC, CPA, and ROAS metrics across multiple product cycles
- Experience in high-stakes, ultra-low-latency real-time decision systems
- Professional experience with ad auctions, ad exchange platforms, and programmatic advertising macro-economics
Languages
Additional
- Hybrid work model requiring 2 days a week at the Berlin campus; must be able to work in a fast-paced environment and lead cross-functional alignment between engineering, product, and data organizations.