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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** LIEFERANDO.DE - **Location:** Teltow, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Code Review, Complex Networks, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Recommender Systems, Software Engineering, SQL Databases, Reinforcement Learning, Git, Apache Flink, Production Code, Data Analytics, Markov - **Published:** July 28, 2026 - **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=2896991386-2 ## About the Role + Advanced proficiency in machine learning methodologies, with extensive experience deploying and managing the full lifecycle of models in production. + Proven experience solving Sequential Decision Making problems in domains such as capacity management, dynamic pricing, inventory control, robotics, recommendation systems, or a wider domain + Deep proficiency in at least one of the following areas, alongside a solid conceptual understanding of the others: Markov Decision Processes, Stochastic Optimization, Reinforcement Learning, or Causal Inference. + Strong Python skills for production-grade code, proficiency in SQL, and solid software best practices (testing, git, code reviews). Experience with feature computation pipelines like Apache Flink is a plus. + Ability to intuitively understand feedback loops and inter-domain effects in complex networks. You prioritize simple, scalable, and effective solutions for complex projects. + Strong leadership skills to guide, mentor, and develop junior data scientists. You excel at fostering team collaboration and a supportive engineering culture. + A holistic approach to project management that bridges operational needs with technical execution. You confidently manage data science solutions from ideation through the full model lifecycle. + Ability to generate innovative ideas and test hypotheses rigorously. You critically analyse approaches, assumptions, and business impact to refine strategies for optimal results. + Strong expertise working within Agile environments to deliver results. You collaborate seamlessly across diverse, cross-functional teams. + Excellent communication skills to translate complex data insights and data science concepts clearly. You can effectively present and tailor your message to both technical and non-technical stakeholders. ## Description As Senior Data Scientist for Logistics, you will take complete technical ownership of building robust, well-engineered, data-driven solutions to exactly these problems. You will drive the vision and execution of data science for your vertical-setting the technical strategy, raising the engineering bar, and directly guiding hard modeling and architectural decisions. Your remit is both deep and broad: you will personally translate our toughest logistics challenges into sophisticated modeling strategies, write clean, production-grade code, and deliver scalable solutions that directly move the metrics that matter. These are some of the key components to the position: + Move beyond static business rules to engineer intelligent, automated systems capable of making high-stakes operational choices under intense real-time uncertainty. + Take complete ownership of the algorithmic policies governing critical logistics inflection points, specifically optimizing order preparation triggers and courier dispatch timing. + Develop machine learning and optimization frameworks designed to mathematically balance conflicting business metrics (e.g., minimizing courier idle time vs. preventing order quality degradation). + Build models that account for cause-and-effect relationships, allowing the platform to identify and adjust for non-compliant partner behaviors and system feedback loops. + Construct robust, scenario-based simulation engines to stress-test hypotheses and validate algorithmic performance under volatile conditions before production deployment. + Drive the entire project pipeline from initial conceptualization and mathematical modeling to live production deployment and continuous A/B experimentation. + Partner closely with Machine Learning and Software Engineers to safely integrate complex, CPU-bound models into our real-time production logistics stack. ## Related Videos - [Are Code Reviews Worth It? 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