PLM Engineering Data Analyst (m/f/d)

Rheinmetall Unterlüß

Stellenbeschreibung:

Overview

Join to apply for the PLM Engineering Data Analyst (m/f/d) role at Rheinmetall

Get AI-powered advice on this job and more exclusive features.

Responsibilities

Introduction of data engineering methods and tools for our 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
Generation of new insights together with our domain and data experts (m/f/d) from our development departments and partners (m/f/d)
Category development to convert these into more 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 the application areas of collaborative engineering and digital management of product development data

What We Are Looking For

Introduction of data engineering methods and tools for our 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
Generation of new insights together with our domain and data experts (m/f/d) from our development departments and partners (m/f/d)
Category development to convert these into more 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 the application areas of collaborative engineering and digital management of product development data

Location

The position can be filled at the Kassel, Kiel, Unterlüß, or Hamburg locations.

What Qualifications You Should Have

Successfully completed degree, e.g., in computer science, engineering, data science, or mathematics, or a comparable qualification 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
Strong communication skills and ability to work in a team

Stärken und Erfahrungen zählen bei Rheinmetall, auch wenn vielleicht nicht alle aufgeführten Anforderungen vollständig erfüllt sind. Wir freuen uns auf Bewerber (m/w/d), die Lust haben, etwas zu bewegen und Verantwortung zu übernehmen. Wir legen Wert auf Individualität und Chancengleichheit. Schwerbehinderte Bewerber (m/w/d) werden bei gleicher Eignung besonders berücksichtigt.

What We Offer You

At our location in Kassel, we offer you:

Work on complete systems
Company pension plan
Employee stock purchase program & profit sharing
Flexible working time models, flexitime model, and VIVA family service
Subsidized lunch and kiosk on site
Fitness and health offerings
Corporate benefits platform with exclusive employee discounts for numerous shops
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

You can find out more about our location and our employees (m/f/d) in Kassel here.

CONTACT INFORMATION

Contact Person: Valeria Wiebe

For questions regarding your application, please use the contact form.