Data Science Academy
Your passion for data science sustains farming, food and planet.
You wish to dedicate your data science expertise to meaningful applications in agriculture? You would like to contribute to shape the future of breeding and farming?
We produce and analyze huge amounts of data at various layers within KWS: From whole-genome sequencing data to drone flights across our fields and market data for our commercial products. We are looking for data science enthusiasts to generate new insights and added value from this treasure trove of data.
You will gain experience with many of these applications and contribute to their further development!
Your quick check
What we offer
- A unique 2-year program to train the next generation of data scientists at KWS.
- Start with a technical onboarding: Learn how to run data science projects at KWS and build networks with other data scientists.
- Multiple assignments of 2-9 month each in different departments, starting with research and development.
- Supervision by domain and technical experts.
- At least one stay (several weeks) at an international breeding station.
- A tailormade training and learning experience.
- Experience in several (at least four) different specialized departments contributing to the manifold digital landscape within KWS.
- Training in programming, software development, data analytics.
- Developing an understanding of added value through digitization.
- International teamwork across continents – while based in Einbeck, Germany.
- Comprehensive and state-ot-the-art training – the perfect prerequisite for creating innovations for farmers, food, and the planet.
- Passion for data and the ability to derive insights from big data.
- University degree (MSc or equivalent) with a focus on data science related subjects.
- Either strong knowledge and experience in data science and an interest in applying it to plant breeding, or a background in agriculture/biology with a strong affinity for data.
- Fluent in at least one programming language such as R, Python, Julia or similar.
- Flexibility and openness to changing teams and working groups, for the diverse assignments. At least one assignment will be abroad.
I like about my job to have free space to develop and improve – both by studying on my own and by exchanging with colleagues.