Data Scientist

Data scientists collect and report on data, and communicate their findings to both business and technology leaders in a way that can influence how an organization approaches a business challenge. They have a solid foundation in computer science, mathematics and algorithms, human behaviour, and knowledge of the industry they’re working in. A data scientist might do the following tasks on a day-to-day basis: Find patterns and trends in datasets to uncover insights; Create algorithms and data models to forecast outcomes; Use machine learning techniques to improve quality of data or product offerings; Communicate recommendations to other teams and senior staff; Deploy data tools such as Python, R, SAS, or SQL in data analysis; Stay on top of innovations in the data science field.
Programming languages

Data scientists can expect to spend time using programming languages to sort through, analyze, and otherwise manage large chunks of data. Popular programming languages for data science include: Python, R, SQL, SAS

Data visualization

Being able to create charts and graphs is a significant part of being a data scientist. Familiarity with the following tools should prepare you to do the work: Tableau, PowerBI, Excel

Machine learning

Incorporating machine learning into your work as a data scientist means continuously improving the quality of the data you gather and potentially being able to predict the outcomes of future datasets.

Big data

Some employers may want to see that you have some familiarity grappling with big data. Some of the software frameworks used to process big data include Hadoop and Apache Spark.


The most brilliant data scientists won’t be able to affect any change if they aren’t able to communicate their findings well. The ability to share ideas and results verbally and in written language is an often-sought skill in data scientists.

80.000 EUR per year

Other IOT professions