Traineeships

Looking for a hands-on learning experience in the exciting field of data visualization and analytics? Look no further! Our Qlik Sense Traineeship offers you the opportunity to gain real-world experience working with cutting-edge technology and impactful data projects.

In today's world of data & analytics, we see more and more opportunities around quality control using vision techniques. You can get started with vision problems using multiple tools and technologies. We want to evaluate the different solutions in the market and list their pro's and con's

As element61, we have been working on the food-forecasting challenge for many years. In this traineeship you will continue leading the way on further optimizing & improving our demand forecasting & simulation set-up.

As a Data Scientist & Data Engineer you want to leverage scalable computing: you want to leverage a compute cluster to run your increasing workloads faster & smoother. For this, we use Spark and often Databricks, our managed Spark platform.

As a Data Analyst or Data Scientist you trust that the data you have access to is correct, complete and of high quality. You want clean data for your analyses, reports & Machine Learning experiments.

Time series is data coming from IoT sensors, smart meters, or digital events. With Tempo, Databricks is introducing a smart way to build transformations on top of times series data. It is an opportunity to leverage this framework into smarter and better time series features for ML predictive models.

In this traineeship, you'll participate in building an internal end-to-end demo set-up. You'll work on different aspects such as the hardware but also the cloud, analytics & data engineering: connecting with the data, transforming it into insights & alerts in the Azure Cloud & Databricks platform.

As a (researching) Data Scientist at element61 you have a solid use case but not always relevant data to test your new machine learning approach or new analytics pipeline. To validate your use cases, you can use synthetic data. The goal of this traineeship is to build a synthetic data generator.

With the EU playing a role as a frontrunner worldwide, the EU Green Deal comes with opportunities and obligations. We want to evaluate the European sustainability standards drafted by EFRAG and the different solutions in the market to respond to these challenges and list their pro's and con's.

In today's world of data & TAX transparency, new software solutions are being developed to support the EU in its role as frontrunner worldwide. We want to compare different solutions in the market to respond to the challenges within different applications in tax reporting.