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# Senior Data Scientist

- **Company:** GXO Logistics
- **Location:** Dormagen, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, BigQuery, Cloud Database, Python (Programming Language), Machine Learning, Azure Machine Learning, SQL Databases, Google Cloud, Model Validation, Information Technology, Data Pipelines
- **Published:** August 9, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=9de2eba5b946192e

## About the Role

* Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field.
 * Master's degree or PhD is an advantage.
 * 5+ years of experience in data science, machine learning, or advanced analytics.
 * Strong expertise in Python and SQL for developing scalable analytical solutions.
 * Hands-on experience with machine learning, statistical modeling, and/or operations research.
 * Proven track record of delivering data science solutions from concept to production.
 * Experience working with large, complex, and imperfect datasets.
 * Strong problem-solving skills and ability to translate ambiguous business challenges into measurable outcomes.
 * Experience with cloud-based data and ML platforms, preferably Google Cloud Platform (GCP).
 * Familiarity with tools such as BigQuery, Vertex AI, Cloud Run, or similar technologies.
 * Strong communication skills with the ability to engage diverse stakeholder groups.
 * Experience in logistics, warehousing, supply chain, retail operations, or similar complex environments is a plus.

## Description

* Design, develop, and validate advanced machine learning, statistical, and optimization models.
 * Solve complex business and operational challenges through data-driven solutions.
 * Partner with product managers, engineers, and business stakeholders to define use cases and success metrics.
 * Identify and leverage relevant data sources to support analytical initiatives.
 * Translate business requirements into scalable data science solutions.
 * Support the productionization, monitoring, and continuous improvement of ML models.
 * Collaborate with AI/ML engineering teams on data pipelines and deployment processes.
 * Communicate insights, model performance, and recommendations to technical and non-technical audiences.
 * Drive experimentation, model evaluation, and performance measurement frameworks.
 * Ensure high standards of scientific rigor, documentation, and best practices.
 * Mentor junior data scientists and provide technical guidance across projects.
 * Influence product and technology decisions through evidence-based recommendations.


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