As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in over 70 countries worldwide, powered by technology, 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 enable creative minds to deliver impactful solutions within our ecosystem. We move fast, take action, and adapt. No matter where you're from or what you believe in, we build, deliver, and lead. We are Delivery Hero.
Job Description
We are seeking a Senior Data Scientist to join our Logistics Optimization team, focused on enhancing delivery experiences.
The Optimization Tribe aims to maximize Delivery Hero's logistics performance by owning and improving algorithms that solve real-time vehicle routing problems, assigning orders efficiently every minute. This directly impacts our core efficiency and customer satisfaction KPIs, influencing decisions across Operations and Product teams.
As a Data Scientist, you will develop ML products that shape our algorithms' logic and decisions, driving efficiency and service quality across our network.
- Lead the design of advanced modeling solutions (ML, Statistics, or Mathematical) to address complex logistics challenges, aligning with business goals and stakeholder needs.
- Develop, implement, and automate data science models and pipelines, including feature generation, retraining, and deployment, using tools like BigQuery and Spark.
- Engage in technical discussions, contribute innovative ideas, and solve modeling challenges alongside peers and leads.
- Translate analytical findings into clear insights to inform stakeholders and improve key business metrics.
- Collaborate with Data & ML Engineering and Tech teams to define data requirements and influence technical roadmaps.
- Deliver high-quality solutions, share knowledge, and contribute to team growth and best practices in a fast-paced environment.
Qualifications- At least 5+ years of experience designing and implementing diverse machine learning models (regression, classification, ensemble methods) with a strong foundation in statistics and probability.
- Expert-level Python skills (pandas, scikit-learn, etc.), proficiency in SQL, and experience building automated ML pipelines using Big Data technologies (BigQuery, Spark) and workflow tools (Airflow, Metaflow).
- Ability to translate business requirements into technical solutions, evaluate assumptions, and ensure data quality.
- Strong communication skills to explain complex concepts and model implications to technical and non-technical audiences.
- Proactive team player with experience collaborating across functions in a dynamic environment. Fluency in English required.
Nice to have:- Experience with Operations Research techniques for logistics optimization.
- Experience in designing and analyzing complex experiments or causal inference methods.
- Skills in building interactive visualizations or dashboards with tools like Streamlit or Plotly Dash.
Additional InformationWe prioritize your well-being and growth:- Hybrid work model with 2 days/week in Berlin.
- 27 days holiday plus additional days based on tenure.
- Educational budget, language courses, parental support, and access to online learning platforms.
- Health and wellness benefits including checkups, meditation, yoga, gym, and bicycle subsidies.
- Financial benefits like Employee Share Purchase Plan, sabbaticals, transportation discounts, insurance, and pension plans.
- Food vouchers, meal discounts, and social events.
Ready to join us? If you're eager to grow, collaborate, and be part of the leading delivery platform, apply today! We value diversity and inclusion and do not discriminate based on race, religion, gender, age, or other aspects. Please inform us of any accommodations or accessibility needs during your application process. Feel free to share your pronouns so we can address you respectfully from the start.