Eric Koenders Email & Phone Number

As an enthusiastic "IT minded" Data Scientist/Specialist, I have a lot of experience in Data Science and Data Engineering. Implementing Data Science tools and analytical pipelines in an organization gives me great fulfillment. This can have a great impact on the way of working in an organization and requires a lot of collaboration with Data Scientists, Data Engineers, Data Analytics, as well as the end users. This is what makes me enthusiastic. I have a lot of experience performing data engineering tasks (standardizing, structuring, transforming and unlocking data) as well as Data Science tasks (e.g. building robust analytical models). Also, I enjoy a lot collaborating in multidisciplinary teams. Naturally, I have broad interests and get a lot of energy from learning and figuring out new things. I am convinced that the best way to grow is to go "out of my comfort zone." My preference is "learning on the job."I am not only a person of (data) content, but also a collaborator and am seen as a connector. I like to work a lot in multidisciplinary teams and get people 'on board'. On the one hand I like to dive deep into the code and on the other hand I am a feeling person who likes to collaborate and connect with colleagues where I also like to share my knowledge and experience. In recent years I have been getting more and more energy from mentoring colleagues. Sharing knowledge is crucial in implementing and maintaining Data Science tools or analytical pipelines ("My job is to put myself out of a job").In my spare time I like to meet up with friends and family and spend a lot of time with my kids. I prefer to exercise every day, read a lot and enjoy making and listening to music.EXPERTISEI enjoy working with and have a lot of experience with R, Python, Docker, Azure Devops (pipelines), Linux, Linear Mixed Models and I learn and discover new things every day when it comes to Azure Cloud (Azure Data Storage , Azure Synapse, Azure Databricks & Azure Data Factory).

Listed skills include Data Mining, Agriculture, Data Analysis, Programming, and 6 others.

• 

  Radboud University

  Molecular Microbiology, Bioinformatics