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# Data Scientist

- **Company:** Seidor
- **Location:** Brussel, Belgium
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Big Data, Data Cleansing, Information Engineering, Python (Programming Language), Machine Learning, Pattern Recognition, Power BI, Tensorflow, Tableau (Software), Pytorch, Retrieval-Augmented Generation, Apache Spark, Keras, Scikit Learn, Splunk, Data Pipelines, Databricks
- **Published:** July 12, 2026
- **Apply:** https://be.indeed.com/viewjob?jk=38181fba3a5f19b4

## About the Role

That's why we are looking for curious individuals who are motivated by challenges and eager to grow personally and professionally, to join our team and make a positive impact on the world through technology., * Degree based on at least four years of study in ICT, STEM or a related field

 * Minimum 8 years of professional experiencein ICT
 * Minimum 4 years of professional experience as a Data Scientist
 * Strong experience with Python and/or R
 * Experience with Power BI and/or Tableau
 * Knowledge of one or more Big Data technologies such as Spark, Databricks, Splunk orHadoop
 * Experience with machine learning frameworks such as Scikit-learn, TensorFlow, Keras or PyTorch
 * Familiarity with Retrieval-Augmented Generation, RAG
 * Experience in data modelling, data quality, machine learning deployment and monitoring

Certifications are not mandatory, although certifications or strong hands-on experience in Python, Power BI, AI/ML, Big Data or data engineering will be considered an advantage.

## Description

We want you to be a part of our team, from Brussels, as a Data Scientist (Duration of the contract: 120 days )

WHAT WILL YOU DO IN YOUR DAY-TO-DAY?

 * Analysing business and customer needs

 * Performing data cleaning, preparation and quality checks

 * Building and maintaining Python data pipelines

 * Creating and maintaining Power BI dashboards

 * Identifying patterns, trends and actionable insights

 * Developing data models

 * Training, deploying and monitoring machine learning models

 * Supporting the integration of ML models into products and services

 * Documenting requirements, changes and deliverables.


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