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# Senior Data Scientist - Data Hub Sales

- **Company:** A11
- **Location:** Köln, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing, Continuous Integration, Customer Data Management, Data Hub, Python (Programming Language), Power BI, SAP (Applications), Software Deployment, SQL Databases, Large Language Models, Snowflake, Machine Learning Operations
- **Published:** June 17, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=158b73e73d0b033a

## About the Role

Do you have experience in Sales?, * Several years of experience in Data Science and Machine Learning, with a strong command of statistical methods, regression models, time series analysis, and modern AI algorithms

 * Advanced proficiency in Python and SQL, with hands-on experience building value-generating solutions in cloud-based environments
 * Proven experience with GenAI use cases such as LLMs, RAG systems, or "talk-to-your-data" interfaces
 * Solid track record building robust ML pipelines and implementing MLOps standards
 * Experience with sales processes, CRM data, and relevant sales KPIs is a strong plus; familiarity with SAP and Power BI is welcome
 * Strong communicator who can present complex analyses clearly to diverse audiences, including senior management
 * Natural mentor with a high level of autonomy, reliability, and a collaborative mindset
 * Fluent in both German and English

## Description

* Design and manage Data Science and AI solutions in Python and SQL on Azure and Snowflake, from proof of concept through to production deployment
 * Take full ownership of large sales dataset analysis and translate findings into clear, actionable recommendations for sales stakeholders
 * Drive collaboration with Data Engineers and Data Analysts to develop KPIs, dashboards, and reporting delivering complex insights through audience-focused data storytelling
 * Own predictive models (forecasting, churn) within the Sales Data Hub and lead proof-of-concept initiatives for new model development
 * Build robust end-to-end ML pipelines and implement MLOps standards including CI/CD, model registry, and monitoring
 * Mentor and guide other Data Scientists, fostering a culture of exploration and professional growth
 * Proactively identify optimization potential and develop new AI and analytics use cases within the sales domain


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