Senior Data Scientist
About The Position
Ready for a challenge? Then Just Eat Takeaway.com might be the place for you. We’re a leading global online delivery platform, and our vision is to empower everyday convenience. Whether it’s a Friday-night feast, a post-gym poke bowl, or grabbing some groceries, our tech platform connects tens of millions of customers with hundreds of thousands of restaurant, grocery and convenience partners across the globe. The Scoober Logistical department enables JET to widen the Restaurant Partner offering to customers, as well as offer various convenience and groceries options that will help empower our customers every convenience moment. About this role Within the Scoober Logistics Operation Department, as a Senior Data Scientist, you will drive the intelligence behind our delivery network. You will sit at the intersection of advanced analytics and operational reality, building the models that decide how we balance supply and demand, optimize courier staffing, and forecast logistical needs across our global markets. Unlike a pure research role, this is a position for a builder. You will lead end-to-end data science and AI projects—from ideation and mathematical modeling to production deployment. You will utilize regression, time-series forecasting, optimization techniques, and GenAI to solve complex logistical puzzles. Furthermore, you will act as a bridge between the data and the operation, using causal inference to measure the real-world impact of our strategies and proactively identifying new opportunities to improve efficiency and courier experience. You will ensure our technical solutions are robust, scalable, and impactful. Please note that this position is located in Amsterdam (3 days a week from our Amsterdam office and 2 days working from home)
Requirements
- Proven experience as a Data Scientist, with a strong portfolio of delivering impactful projects in a commercial environment.
- Deep theoretical and practical knowledge of Time Series Forecasting (e.g. ARIMA) and Regression analysis.
- You are comfortable writing production-quality Python code.
- Experience with MLOps tools, containerization (Docker), and orchestration (Airflow/Dagster) is essential.
- Experience with Cloud platforms (GCP preferred, or AWS/Azure) and handling large datasets via SQL/BigQuery.
- A proactive mindset with the vision to spot new opportunities for data-driven improvements in a physical logistics network.
- Excellent communication skills in English, with the ability to explain complex AI concepts to non-technical stakeholders and influence decision-making.
Nice To Haves
- Plus to have experience with Optimization techniques (Linear Programming, Heuristics), Causal Inference frameworks and AI engineering.
- Experience in Logistics, Supply Chain, or On-Demand delivery industries is a strong asset.
Responsibilities
- Project Leadership & Innovation: Take full ownership of complex data science projects from the initial "what if" question to final delivery. Proactively identify opportunities within logistics operations where machine learning or optimization can drive efficiency, cost-savings, or service improvements.
- Advanced Modeling & Optimization: Develop and refine sophisticated models using regression and time-series forecasting to predict order volume and courier supply. Apply mathematical optimization techniques to solve routing, zoning, and shift-planning challenges.
- AI Engineering & Production: Go beyond the notebook. Design and deploy production-grade code and machine learning pipelines. Ensure your models are scalable, maintainable, and integrated seamlessly into our cloud infrastructure.
- Causal Inference & Experimentation: Move beyond correlation. Apply causal inference methods to understand the true impact of operational changes (e.g., pay scheme adjustments, zoning changes) on the broader logistics network.
- Stakeholder Partnership: Act as a technical partner to Operations leadership. Translate complex mathematical outcomes into clear, actionable business recommendations that shape the future of our logistics network.
- Mentorship & Best Practices: Champion high coding standards and data science best practices within the team. Conduct code reviews and guide people through technical roadblocks.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
1-10 employees
