About Cheryl

I am a data scientist.

Since August 2018 I am working at Coolblue, in their core data science team. Here I am working on projects involving topics such as recommender systems, bidding management and dynamic pricing.

Before that I was following a traineeship at Xomnia for which I was working 4 days a week at the Operations Research department at Airfrance-KLM. There, I was working on several recommender systems in order to provide the customer data-driven and personal recommendations using Pyspark on an Hadoop cluster.

Besides my work and studies, I also have a great passion for travelling, animals & the environment, cooking, eating & drinking with friends & family, coffee, and my turtles.



  • Python
  • R
  • Pyspark
  • Git
  • SQL


  • Apache Spark
  • Hadoop
  • Linux
  • Qlikview
  • MongoDB
  • Airflow
  • Several CI tools

Knowledge / Fields

  • Data Science
  • Machine Learning
  • Artificial Intelligence
  • Big Data
  • Natural Language Processing
  • Computer Science
  • Software Development
  • Predictive Analytics


At Coolblue I am working on projects such as recommender systems, bidding management and dynamic pricing. We mainly use python for this, and R and RShiny for our dashboards. We have implemented a succesfull recommender system which predicts products for our customers and is mainly used for our emails. Also, we have productionized a model which predicts our bids for Google Adwords. Currently we are working on dynamically pricing our products in order to achieve the business goals.

Before this I was a data science trainee for Xomnia and KLM. At the operations research department, specifically the customer data management team, I was doing data science projects in Spark using mainly Pyspark and Python. In that year we successfully developed and put into production six recommender systems and one text mining project leading to great results in terms of click through rate and conversions of our customers. I worked together with the scrum team using Git to do code reviews, pull requests and versioning of our code. Through Bamboo build plans we delivered our models to the production platform and ensured a continuous integration.


MSc Data Science

Master's degree Information Studies: Data Science at the University of Amsterdam.

Extra courses

* Machine Learning - Stanford University
* Cambridge Certificate in Advanced English
* The Unix Workbench - Johns Hopkins University

BSc Aviation Engineering

Graduated with honours at the Aviation Academy of the University of Applied Sciences in Amsterdam.


VWO Nature & Technology / Nature & Health with extra math courses.

June 2017 I finished my master’s degree in Data Science at the University of Amsterdam for which I focused on machine learning of unstructured data and graduated in the digital marketing field at KLM.  For my thesis I developed an approach of clustering website visitors based on contextual information and data on their searched destination(s) in order to distinguish user profiles which reflect their similar interests and/or behaviour which can be used for further recommendations. This project was conducted mostly in Python using several machine learning algorithms.

I have a background in Aviation Engineering where I developed my interest in aircraft performance, aerodynamics, dynamic systems analyses & modelling and mathematics. In my final year I got accepted for the honours programme and got a taste for Data Science. Focusing my final year and graduation in this field, I wrote my thesis on predictive maintenance of aircraft components. Following the CRISP Data Mining methodology, I developed a predictive model in R which analyses and visualizes component replacement using text mining on maintenance logs and anomaly detection on error messages from equipment sensors. 

I have also completed several courses such as the Machine Learning course by Stanford University, the Cambridge Certificate in Advanced English and The Unix Workbench by Johns Hopkins University.