Job Description
As a Data Scientist / Data Engineer you will design, implement, and maintain advanced data pipelines and analytical frameworks that feed into cutting-edge AI models. You will collaborate with machine learning engineers, AI architects, and domain experts to ensure datasets are high-quality, well-structured, and optimized for model training and deployment. By transforming raw data into actionable insights, you will be a crucial enabler of scalable, reliable AI solutions for real-world energy applications.
Key Responsibilities
Data Engineering
- Design, build, and optimize scalable data pipelines for acquiring and processing large, complex datasets (e.g., IoT sensors, 2D / 3D imaging).
- Implement and manage ETL (Extract, Transform, Load) processes to prepare data for AI model training.
- Monitor and maintain data integrity, quality, and accessibility throughout the AI development lifecycle.
- Develop and enforce standards for data governance, storage, and security.
Data Science
Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns relevant to AI objectives.Conduct data preprocessing, feature engineering, and labeling to create machine learning-ready datasets.Collaborate with machine learning engineers to inform model architecture choices and training strategies.Validate AI models by applying advanced statistical analysis and performance evaluation metrics.Collaboration & Integration
Partner with multidisciplinary teams to integrate trained AI models into operational systems.Ensure data workflows and model pipelines are reusable, flexible, and well documented for future development cycles.Support iterative improvement processes by analyzing model performance and adjusting data inputs accordingly.Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.Proven experience in data engineering and / or data science, preferably with large-scale sensor or geospatial data.Proficiency in Python, SQL, and ML frameworks such as TensorFlow or PyTorch.Familiarity with 2D / 3D data formats, point cloud processing, and GIS tools is a strong plus.Solid understanding of machine learning concepts and experience supporting AI / ML model development.Strong analytical and problem-solving skills, with attention to detail and data quality.Excellent communication skills in English (spoken and written); German is a plus.Ability to work independently and collaboratively in a fast-paced, agile environment.Preferred Qualifications
Experience with DevOps, CI / CD pipelines, and containerization (Docker, Kubernetes).Knowledge of MLOps practices and model deployment in production environments.Familiarity with scientific literature and research best practices.