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# (Senior) Applied Scientist (Machine Learning)

- **Company:** HUK-COBURG Versicherungsgruppe
- **Location:** Coburg, Germany (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Neural Networks, Computer Programming, Data Validation, Python (Programming Language), Machine Learning, Recommender Systems, Unstructured Data, Deep Learning, Information Technology, Data Analytics
- **Published:** September 12, 2026
- **Apply:** https://www.adzuna.de/details/5878103621

## About the Role

* A completed degree (at least a master's, ideally a Ph.D.) in data science, machine learning, mathematics, physics, economics, computer science, or a related field
 * Several years of professional experience as a Data Scientist (f/m/d), Machine Learning Engineer (f/m/d), or in the field of Advanced Analytics, ideally with a focus on marketing, customer analytics, or data-driven business models
 * In-depth knowledge of machine learning, statistical modeling, predictive analytics, and the development of productive data science solutions
 * Strong programming skills in Python and in-depth theoretical and practical knowledge of modern machine learning techniques and tools
 * Ideally, experience with causal inference, uplift modeling, recommender systems, or personalization solutions
 * A solution-oriented, hands-on approach that embraces experimentation, with a high degree of personal responsibility and a willingness to take ownership of projects and results
 * Hybrid work model: Willingness to work on-site in Coburg

## Description

* Design, development, and refinement of modern machine learning, deep learning, and statistical models for business-critical problems with high strategic impact
 * Analysis of complex structured and unstructured data (e.g., text, documents, time series) and development of suitable modeling approaches for predictive analytics, forecasting, and anomaly detection
 * Application and evaluation of modern ML and DL methods, including neural networks and transformer-based models for unstructured data
 * Planning, conducting, and evaluating experiments, as well as developing and validating data-driven hypotheses to support decision-making within the company
 * Translating scientific insights from machine learning, deep learning, statistics, and optimization into robust, production-ready applications
 * Development and operation of scalable, reproducible ML and DL pipelines using modern MLOps standards with a focus on stability, scalability, and traceability


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