Job Description
Source is seeking a talented person who is driven to push the boundaries of the status quo and explore the unknown. You'll partner with our CTO & Director of Data Science to create ground-breaking technology. This is an incredible opportunity to bring positive change to the global food system. At Source we are building an international, multi-disciplinary team consisting of the brightest talents that the fields of computer & data science, engineering, and agronomy have to offer. As a data scientist at Source, you will be working on statistical models that predict and control plant growth and climate in high-tech greenhouses.
What we’d love you to get excited about
Using time-series and machine learning techniques to predict and optimize the greenhouse climate & plant phenotype
Designing, training, and deploying machine learning models
Building models and data transformation pipelines, and integrating them into existing products
Owning your work end-to-end, with opportunities to show initiative and define your course of action, gradually expanding your scope
Collaborating with our growing team of data scientists to brainstorm & tackle our challenges in the best possible way
Working in a multi-disciplinary environment with specialists in engineering and agronomy
Working hand-in-hand with growers to deeply understand the problems at stake & defining ways to solve them
Supervising and developing a team of junior data scientists
Requirements
You have a natural curiosity and you love to find the right solution for a specific problem. We expect you to be especially eager to learn the Plant Science aspect of our business which is critical to the success of our models. Further, you have:
MSc or Ph.D. degree in a quantitative discipline
3+ years experience working as a data scientist
Applied experience with machine learning libraries, preferably using Python
Experience in applying data science methods to real-life problems
Good presentation and communication skills with the ability to explain complex analytical concepts to people from other fields
Bonus points
If you have experience with optimization methods (e.g. linear programming, gradient descent, optimal control)
If you have experience with developing end-to-end models, from ideation to deployment in the cloud (AWS)
If we can invite you for a game of Padel (yes, there is a Padel court in our building)