Decision Scientist
Role details
Job location
Tech stack
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?"
- 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.
- 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.
- Quantify Trade-offs: You will build economic and simulation models to quantify the intricate trade-offs between customer experience (e.g., delivery speed) and operational efficiency (e.g., cost per order), delivering clear ROI-based recommendations.
- 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.
- 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.
Requirements
Do you have experience in SciPy?, Do you have a Master's degree?, We are looking for a first-principles thinker with a deep passion for understanding complex systems and driving decisions with data.
- Education: A Master's degree in a quantitative field such as Economics, Statistics, Computer Science, Operations Research, or a similar discipline.
- 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.
- 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 (e.g., Difference-in-Differences, Regression Discontinuity, Instrumental Variables).
- A robust statistical foundation, particularly in hypothesis testing and modeling.
- 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 (e.g., CausalML, DoWhy).
- Business Acumen: The ability to translate ambiguous business problems into a logical, analytical framework and to communicate complex scientific concepts to non-technical stakeholders.
Benefits & conditions
- A unique opportunity to have a massive impact on the core technical systems of a leading quick commerce company.
- A highly intellectual and collaborative environment where you can apply cutting-edge methods to solve real-world problems.
- 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
- 26 days of vacation, +1 day every year up to a maximum of 30 days
- A mobility budget of 35 EUR per month for Deutschland Ticket subsidy
- A cool discount on your Urban Sports Club membership
- Attractive company pension options
- Unlimited access to an e-learning and development platform, MyAcademy, including online German courses
- Online discounts with Corporate Benefits and Future Bens
- A cool discount off your personal Flink orders; be the first to test out new products!
- A modern and dog-friendly office in the heart of Berlin - lots of delicious lunch spots available within short walking distance
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