Data Scientist

Dortmund

Data Scientist

YOUR TASKS:

• Development, training and evaluation of machine learning models, e.g. for regression, classification, time series forecasting and anomaly detection, as well as models for image and video analysis.
• Analysis, processing and quality assurance of large, heterogeneous datasets (e.g. sensor, image, and operational data)
• Feature engineering, selection of suitable modeling approaches and hyperparameters taking into account functional requirements, technical framework conditions and operational restrictions.
• Implementation of ML models in robust, production-like code structures
• Close collaboration with the specialist departments to translate technical questions into data-driven use cases and model approaches.
• Documentation of models, data assumptions, results and limitations to ensure traceability, governance requirements and maintainability.
• Support in transferring models into productive IT systems in collaboration with AI Integration Engineers, software development and IT operations.
• Contributing to the further development of data, feature and model standards as well as best practices for machine learning and MLOps within the company.

YOUR PROFILE:

• Completed university degree in computer science, business informatics, engineering or a comparable field of study
• Several years of practical experience in the design, implementation and evaluation of classic machine learning methods in real-world applications.
• Solid theoretical understanding of a wide range of common statistical methods and machine learning models.
• Excellent programming skills in Python as well as experience with common ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost) and AzureML
• Solid experience with time series analysis and forecasting as well as computer vision
• Experience with reproducible model development and version control systems
• A highly structured and analytical approach to work, high quality standards, and meticulous documentation.
• High level of personal responsibility and pragmatism in finding solutions
• Enjoyment of working in an interdisciplinary team and jointly developing practical AI solutions.
• Excellent communication and cooperation skills, as well as experience as part of an interdisciplinary team.