Data Scientist developing data-driven software solutions for AIXTRON's deposition systems. Analyzing complex data, implementing predictive models, and collaborating with data engineering teams.
Responsibilities
Analyze and prepare complex data from various sources to derive actionable insights.
Work closely with domain experts to understand requirements and develop data-driven solutions.
Develop and implement models for predictive maintenance, time series analysis, and anomaly detection.
Collaborate with the data engineering team to generate new insights from structured and unstructured data.
Present and visualize results and models effectively, e.g., using Plotly Dash.
Take responsibility for deploying your solutions to production environments.
Ensure deployed models are monitored, maintained, and updated throughout their lifecycle.
Actively contribute to continuously improving and keeping our ML solutions up to date.
Requirements
Degree in Data Science, Computer Science, Mathematics, Physics, or a comparable field.
Strong experience in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn).
Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
Experience with CI/CD, containerization (Docker/Podman), and REST APIs or similar interfaces.
Comfortable working in Windows and Linux environments.
Knowledge of data visualization (e.g., Plotly Dash) and handling large datasets.
Understanding of deployment, monitoring, and lifecycle management of ML solutions.
Creativity, the ability to work independently, and strong problem-solving skills.
No fear of large datasets — even though we do not operate a classical big-data setup.
Knowledge of the semiconductor industry is a plus but not required.
Benefits
Flexible working hours: You can arrange your working hours flexibly without fixed core hours, work remotely, and switch between the office and mobile working.
Health: We support your physical and mental well-being through regular health initiatives.
Development: We prioritize your continuous development — through our AIXTRON Academy or individualized support programs.
Corporate Benefits: You benefit from exclusive discounts with numerous partners as part of our Corporate Benefits program.
Open corporate culture: We maintain an open and respectful “du” (informal first-name) culture across all hierarchy levels.
Senior Associate at PwC focusing on data analytics to drive insights and guide client strategies. Involves advanced techniques and collaboration on AI and GenAI solutions.
Data Scientist responsible for analyzing complex data sets and developing methods to create actionable insights. Collaborate with engineering teams to improve data quality and deliver business value.
Senior Director driving product development in data science for TransUnion. Leading initiatives in AI and analytics for the Specialized Risk portfolio.
Data & Analytics Lead at AstraZeneca driving data - driven solutions in clinical product development. Leading teams and collaborating with stakeholders across global platforms.
Mid - Level Engineering Data Scientist for Boeing's Global Services Analytics team. Creating analytics models and collaborating on health management solutions for KC - 46 platform.
AI expert managing predictive modeling and statistical validation for TEHORA. Integrating predictive models into API architecture and producing performance metrics.
Head of Data Strategy leading and developing data initiatives for Zurich's GI Business. Focusing on data strategy, governance, and analytics while fostering collaboration across teams.
Medical Analyst analyzing engagement effectiveness with advanced analytics solutions aligned with Medical business strategies. Collaborating with cross - functional teams to provide insights for US Medical Affairs.
Research Fellow/Trainee in Women's Health using Data Science and Health Information Technology. Developing interdisciplinary research skills and methodologies focusing on health research.
Senior Data Scientist developing Asset Management Analytics for Queensland Rail. Contributing to organisational KPIs and enhancing asset performance through data analysis and modelling.