PLM Engineering Data Analyst (m/f/d)

Das ist der Job

Generation of new insights together with domain and data experts.

Darum lohnt es sich

Strong communication skills and ability to work in a team. Benefits Work on complete systems. Corporate benefits platform with exclusive employee discounts for numerous shops. Responsibilities Introduction of data engineering methods and tools for product management databases as part of development-centered product lifecycle management (PLM).

Development of intelligent, scalable, reusable, and reliable solutions and methods for data analysis, integration, cleansing, and processing. Category development to convert insights into informative data structures using clustering and classification algorithms.

Development of machine learning models, especially in the areas of clustering, classification, and text analysis. Defining and implementing requirements within the framework of data storage and processing systems. Supporting the automatic provision of engineering data for collaborative engineering and digital management of product development data.

Qualifications Successfully completed degree or a comparable qualification, e.g., in computer science, engineering, data science, or mathematics, with a focus on data science or data analytics. In-depth experience with semantic analysis methods (e.g., natural language processing) for the structured evaluation of text-based data.

Good knowledge of database queries and automation with SQL, PowerShell scripts, PowerBI, data visualization, and data queries, as well as object‑oriented software development. Professional experience with PLM databases and data models is an advantage.

Knowledge of NLP frameworks (e.g., spaCy, NLTK, transformers) and ML libraries such as scikit‑learn or PyTorch/TensorFlow is desirable. High willingness to understand complex data models, grasp semantic relationships, and analytically process domain‑specific knowledge. Very good written and spoken German and English skills. Company pension plan.

Employee stock purchase program and profit sharing. Flexible working time models, flexitime, and VIVA family service. Subsidised lunch and on‑site kiosk. Fitness and health offerings. Discounted job ticket. Individual and diverse external and internal development opportunities, including at the Rheinmetall Academy.

Professional induction process accompanied by a digital onboarding tool. Equality and Inclusion Stärken und Erfahrungen zählen bei Rheinmetall, auch wenn vielleicht nicht alle aufgeführten Anforderungen vollständig erfüllt sind. Wir legen Wert auf Individualität und Chancengleichheit.

Schwerbehinderte Bewerber (m/w/d) werden bei gleicher Eignung besonders berücksichtigt. Contact Information Contact Person: Sherin Schümchen For questions regarding your application, please use the contact form. #J-18808-Ljbffr