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# Data Scientist

- **Company:** LIEFERANDO.DE
- **Location:** Berlin, Germany (Remote available)
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Unit Testing, Microsoft Basic Data Partition, Big Data, Data Cleansing, Data Security, Data Structures, Data Visualization, Python (Programming Language), Machine Learning, SQL Databases, Backend, Git, Pandas, Scikit Learn, Software Version Control
- **Published:** October 17, 2026
- **Apply:** https://www.adzuna.de/details/5931601007

## About the Role

* Practical, hands-on experience building and validating ML models - comfortable working independently under general supervision, while knowing when to seek guidance from more senior colleagues.Familiarity with statistical and machine learning techniques (classification, regression, clustering, decision trees) and how to select the right one for a given problem.
 * Intermediate-to-advanced proficiency in Python (pandas, scikit-learn) and SQL; familiarity with industry style guides such as PEP 8.
 * Ability to perform data cleaning (de-duplication, standardisation) and exploratory data analysis; awareness of data security, compliance, and quality assessment.
 * Familiarity with version control (Git), testing, and basic data pipelines.
 * A strong interest in logistics is a plus.

## Description

As a Data Scientist on the Estimations team, you will help build the predictive engine that powers our global delivery network - developing the machine learning models that predict Estimated Time of Arrivals (ETAs), considering factors like courier-finding, drive times, preparation times, rejections, and delays. Your mission is to apply practical knowledge to build, validate, and maintain ML models that predict logistics outcomes with accuracy and reliability. You will collaborate closely with Senior Data Scientists, Backend Engineers, and Machine Learning Engineers, transforming stakeholder needs into actionable methodologies. As a developing professional, you will work independently with general supervision while actively seeking guidance to grow your technical and stakeholder skills.

These are some of the key components to the role:

 * Model Development & Assessment: Lead well-defined assignments to develop and maintain machine learning models (regression, classification, clustering). Run predictive analyses and perform validation and enhancement activities to improve ETA accuracy.
 * Data Analysis & Engineering: Use SQL and Python to acquire, transform, and clean large-scale data sets. Apply appropriate techniques for outliers, missing values, and exploratory data analysis to create data structures relevant to logistics problems.
 * Production Standards: Apply engineering practices to your work - intermediate-level source code, unit tests, version control. Be mindful of production environment rules and help monitor predictive performance of models.
 * Process Improvement: Identify opportunities to automate or improve existing processes; recommend solutions based on established best practices.Actionable Insights: Translate analytics output into clear, actionable insights for decision-making. Assist in presenting these to stakeholders in easy-to-understand language, using data visualisation where appropriate.
 * Cross-functional Collaboration: Work closely with Backend and ML Engineers; participate in cross-functional projects, building business acumen and domain knowledge from collaborating colleagues.
 * Problem Solving: Solve problems independently and propose solutions to complex logistics problems. Suggest project timelines and help set expectations for deliverables.