Jonas Cristens, Data Warehouse Design Developer in Grimbergen, Belgium
Jonas Cristens

Data Warehouse Design Developer in Grimbergen, Belgium

Member since August 17, 2019
Jonas is an SQL/ETL developer and data scientist, and for the past few years, he's worked at Exellys—a top Belgium consultancy company—mainly with insurance and private banking companies. As an SQL developer, Jonas has automated financial reporting for a national bank and built a data quality framework along with multiple dashboards, and as a data scientist, he's analyzed customer behavior and financial transactions using machine learning.
Jonas is now available for hire




Grimbergen, Belgium



Preferred Environment

Git, Linux, Jupyter Notebook, PyCharm, DataGrip

The most amazing...

...project I've developed is a customer churn model which allows the bank to retain customers who are about to churn by taking the appropriate actions.


  • Data Scientist

    2019 - PRESENT
    Delen Private Bank (via Exellys)
    • Analyzed fraudulent transactions and created a classification model to detect fraudulent transactions (financial transaction analysis).
    • Created a model to segment customers into different groups based on data (customer behavior analysis). This enabled the company to better target customers with relevant events.
    • Set up a data warehouse and provided technical follow-up of the development where data from different operating systems are merged together for reporting purposes.
    • Designed the model of the data warehouse where data from the different operating systems are merged together for reporting purposes.
    • Created operational, management and executive dashboards to support the company.
    • Constructed a model to predict when a customer is about to churn and recommend appropriate action to management to prevent the customer from churning (customer churn model development).
    Technologies: IBM Db2, Microsoft SQL Server, Microsoft Power BI, Python, SQL
  • ETL/Data Warehouse Developer

    2017 - 2018
    Belfius Insurance (via Exellys)
    • Automated the generation of financial documents which contains data from different data sources.
    • Implemented the ability to quickly detect corrupt input data in financial reports; corrupt data is a big problem when reporting to the national and international authorities due to the loss of precious time. The company now detects corrupt input data 50% faster and saves a lot of money.
    • Constructed a generic data quality framework which allows the company to improve the operational systems and fix the bugs which are found during the process of analyzing the data.
    • Designed a generic data quality framework including the high-level architecture and data model.
    • Created the design of management and operational dashboards to provide the company with qualitative insights and improve the overall business.
    Technologies: SAS Visual Analytics, SAS Data Integration (DI) Studio
  • Data Engineer (Internship)

    2017 - 2017
    Big Industries
    • Built a Yum repository server which allows one server to function as the only with an internet-connected node in the network of the data center and provide the rest of the nodes with packages and updates.
    • Installed and protected (Kerberize) a Hortonworks cluster.
    • Let TensorFlow run on a Kerberized cluster using Apache Slider to distribute the computation of AI models.
    Technologies: CentOS, Linux, Apache Spark, TensorFlow, Hadoop


  • Kickstarter Analysis

    Predict and analyze which Kickstarter projects will be successful or not. Also, analyze which parameters influence the probability of success and visualize the insights in an easy-to-interpret manner.

  • Millennium Development Goals

    This project is an analysis of the different development indicators in the world to see if the world is getting better overall or not.

    During these analyses, I analyzed the consumption of energy, the poverty rate per headcount in the world, and the major health indicators in the world. These numbers give us insights into the general progress of the world.

  • Titanic

    I developed a prediction model to predict which passengers will survive or not. It also analyzes which factors influence your chances of survival.

    It also reports the most critical indicators in an easy-to-understand way so that everybody who reads this analysis can understand it and draw the correct conclusions.

  • Market Basket Analysis

    I developed a model to see which products are frequently bought together. This model will provide the company with insights on how to position products and recommend specific ones to customers.


  • Languages

    SQL, Python 3, Python, Scala, Java
  • Libraries/APIs

    Scikit-learn, Pandas, TensorFlow, NumPy, Matplotlib, Keras
  • Tools

    Tableau, DataGrip, PyCharm, Git, Microsoft Power BI, SAS Data Integration (DI) Studio
  • Paradigms

    Business Intelligence (BI), Data Science, ETL, Agile, REST
  • Storage

    Relational Databases, Microsoft SQL Server, IBM Db2, SQL Server 2017, SQL Server Integration Services (SSIS)
  • Other

    Data Warehouse Design, Data Warehousing, Data Visualization, Data Modeling, Dashboards, Machine Learning, Data Analysis, Exploratory Data Analysis, SAS Visual Analytics
  • Frameworks

    Hadoop, Apache Spark
  • Platforms

    Jupyter Notebook, CentOS, Docker, Linux


  • Master's Degree in Data Science
    2018 - 2019
    Barcelona Technology School - Barcelona, Spain
  • Master's Degree in Data Science
    2018 - 2019
    University of Barcelona - Barcelona, Spain
  • Bachelor's Degree in Information Management and Security
    2014 - 2017
    Thomas More - Mechelen, Belgium


  • Certificate of Graduation
  • Data Science
    JUNE 2018 - PRESENT
    Crunch Analytics
  • General Introduction to Insurance
    MAY 2018 - PRESENT
  • SAS Data Integration Studio
  • Object-oriented Programming in Java

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