Data Scientist 2


  • Normally computer science with a concentration in maths


  • statistical data analysis
  • works from a set of assumptions and develops models that he uses in addition to structured/relational data to analyse a large amount of unstructured data
  • uses principles such as predictive modelling, machine and/or deep learning
  • likes finding answers to questions himself, so a good knowledge of the industry is an advantage
  • presents findings to decision-makers and these, as a rule, have direct consequences on the business or on the business model of the organisation
  • Projects are completed as part of his deployment.

Operating systems

  • Programming languages: e.g. Python, Java, Julia, R, SQL, Scala, Ruby, Clojure
  • Tools: e.g. SPSS, Tableaut, QlikView, Hadoop, MongoDB, Hive, Spark, SAS, MATLAB, Knime