Job Description
As a Decision Scientist, you will be the expert on cause and effect within our logistics network. Your primary responsibility will be to answer the most critical strategic questions facing our business: "What should we do, and why?"
1. Go Beyond Correlation: You will establish causality in a complex, real-time environment, providing the business with a clear and defensible understanding of how our actions impact outcomes.
2. Drive Experimentation: You will design, launch, and analyze complex experiments (A/B/n tests) to measure the precise impact of changes to our dispatching algorithms, rider incentives, and customer promises.
3. Quantify Trade-offs: You will build economic and simulation models to quantify the intricate trade-offs between customer experience (, delivery speed) and operational efficiency (, cost per order), delivering clear ROI-based recommendations.
4. Employ Advanced Causal Inference: When clean experiments aren't feasible, you will leverage a sophisticated toolkit of econometric and causal inference techniques to measure the impact of product launches and operational changes on our marketplace.
5. Influence High-Level Strategy: You will partner directly with key stakeholders in Product, Engineering, Data (Science) and Operations to translate your findings into high-impact business strategy, fundamentally shaping the future of our dispatching roadmap.
Qualifications
We are looking for a first-principles thinker with a deep passion for understanding complex systems and driving decisions with data.
6. Education: A Master's degree in a quantitative field such as Economics, Statistics, Computer Science, Operations Research, or a similar discipline.
7. Experience: 2+ years of professional experience in a Decision Science, Applied Science, Data Science, or quantitative strategy role, with a proven track record of using data to influence critical business decisions.
8. Core Competencies:
A deep, practical knowledge of experimental design (A/B testing, Switchback testing) and statistical analysis.
A strong grasp of econometrics and causal inference methods (, Difference-in-Differences, Regression Discontinuity, Instrumental Variables).
A robust statistical foundation, particularly in hypothesis testing and modeling.
9. Technical Skills:
Expert-level SQL.
High proficiency in Python or R for data analysis and modeling, with experience using libraries such as Pandas, Statsmodels, SciPy, or causal inference packages (, CausalML, DoWhy).
10. Business Acumen: The ability to translate ambiguous business problems into a logical, analytical framework and to communicate complex scientific concepts to non-technical stakeholders.
Additional Information
11. A unique opportunity to have a massive impact on the core technical systems of a leading quick commerce company.
12. A highly intellectual and collaborative environment where you can apply cutting-edge methods to solve real-world problems.
13. A €1000 annual L&D budget as well as individual coaching options to ensure you have plenty of opportunities to learn, grow and achieve your goals
14. 26 days of vacation, +1 day every year up to a maximum of 30 days
15. A mobility budget of 35 EUR per month for Deutschland Ticket subsidy
16. A cool discount on your Urban Sports Club membership
17. Attractive company pension options
18. Unlimited access to an e-learning and development platform, MyAcademy, including online German courses
19. Online discounts with Corporate Benefits and Future Bens
20. A cool discount off your personal Flink orders; be the first to test out new products!
21. A modern and dog-friendly office in the heart of Berlin - lots of delicious lunch spots available within short walking distance
It is our commitment that every applicant will be evaluated according to their skills regardless of age, gender identity, ethnicity, sexual orientation, disability status, or religion.