At Daiichi Sankyo, we are united by a single purpose, to improve lives around the world through innovative medicines. With a legacy of innovation since 1899, a presence in more than 30 countries, and more than 19,000 employees, we are advancing breakthrough therapies in oncology, cardiovascular disease, rare diseases, and immune disorders. Guided by our 2030 vision to "be an innovative global healthcare company contributing to the sustainable development of society", we are shaping a healthier, more hopeful future for patients, their families, and society.
The Position
Join our interdisciplinary team and contribute to impactful projects that drive pharmaceutical innovation. You'll work closely with scientists and engineers to support and accelerate pharmaceutical development and manufacturing activities through data-driven methods. For our production site in Pfaffenhofen we're looking for a
Working Student (m/f/d) Technology Innovation Strategy & Intelligence
Roles and Responsibilities
- Develop and maintain Python-based data engineering pipelines
- Support exploratory data analysis and machine learning model development
- Contribute to data visualization and dashboarding for scientific and operational insights
- Optionally support physics-based modeling projects (e.g. CFD simulations, molecular modeling, or mechanistic models)
- Collaborate across departments to understand data requirements and help solve complex scientific challenges
Education & Experience
- You are currently enrolled in a Master’s or advanced Bachelor’s program in Computer Science, Data Science, Engineering, Physics, Chemistry, Life Sciences, or a related field
- Solid programming skills in Python, including common libraries (e.g., pandas, NumPy, scikit-learn, matplotlib)
- First experience with data wrangling, data visualization, or modeling
- Familiarity with VS Code, Jupyter Notebooks, Git, and basic software development workflows
- Strong analytical thinking, a self-driven mindset, and a passion for science and technology
- Optional: Interest or experience in physics-based modeling, mechanistic simulation, computational fluid dynamics (CFD), or molecular modeling
