Data Scientist

TechNET; Brussel; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

TechNET is seeking an experienced Data Scientist & Data Engineer for a hybrid contract in Brussels. You will own the full data lifecycle from exploration to production-ready delivery, leveraging Python, ML, and data engineering practices across large-scale datasets.

You will build scalable ETL/ELT workflows, with cloud-based processing and geospatial analytics, delivering dashboards and insights to technical stakeholders and partners.

Qualifications

• Master's degree or equivalent in Data Science, CS, AI, Mathematics or related field.
• Proven experience with data science and data engineering.
• Strong project experience delivering production-ready ML solutions.

Responsibilities

• Analyse and transform large, complex datasets from multiple sources.
• Design scalable data pipelines using Python and modern data engineering practices.
• Build, test and optimise ML models including supervised/unsupervised learning.
• Perform statistical analysis, time-series modelling and anomaly detection.
• Work with geospatial data and location-based analytics.
• Develop ETL/ELT workflows and improve data quality.
• Transform PoC models into production-ready solutions.
• Utilise cloud technologies for data processing, storage and deployment.
• Develop dashboards and visualisations to communicate findings.
• Collaborate with engineering teams and external partners to deliver data-driven solutions.

Skills

Python

Data engineering

Machine learning

SQL

Cloud

Geospatial analytics

Software engineering

Data visualization

IoT / telemetry

Time-series analysis

Deep learning

Computer vision

Generative AI

Distributed data processing

NoSQL databases

Productionalization

Education

Master's degree or equivalent in Data Science/CS/AI/Mathematics

Tools

pandas

NumPy

scikit-learn

GeoPandas

Git

Docker

AWS

Job description

Location: Brussels, Belgium – Hybrid role Contract: Initial engagement until March 2027, with potential for 12-month extensions

We are working with an established international technology organisation looking to engage an experienced Data Scientist & Data Engineer on a contract basis.

This is an opportunity to work on complex, large-scale datasets, combining data science, machine learning and data engineering to develop reliable, scalable and commercially valuable analytical solutions.

The successful consultant will take ownership of the full data lifecycle, from exploration and modelling through to validation, automation and production-ready delivery.

Key Responsibilities

• Analyse, clean and transform large, complex datasets from multiple sources.
• Design and develop scalable data pipelines using Python and modern data engineering practices.
• Build, test and optimise machine learning models, including supervised and unsupervised learning techniques.
• Perform statistical analysis, time-series modelling, anomaly detection and predictive analytics.
• Work with geospatial datasets, including spatial processing, mapping and location-based analytics.
• Develop automated ETL/ELT workflows and improve data quality, reliability and performance.
• Transform proof-of-concept models into maintainable, production-ready solutions.
• Utilise cloud technologies to manage data processing, storage and deployment.
• Develop dashboards, visualisations and analytical reports to communicate findings.
• Collaborate with engineering teams, technical stakeholders and external partners to deliver data-driven solutions.

Technical Requirements

• Python: Strong commercial experience with pandas, NumPy, scikit-learn and data processing libraries.
• Data Engineering: Experience developing ETL/ELT pipelines, automating workflows and managing large datasets.
• Machine Learning: Practical experience with statistical modelling, feature engineering, model evaluation and anomaly detection.
• SQL: Strong database querying and data manipulation skills.
• Cloud Technologies: Experience working with cloud-based data environments, ideally AWS.
• Geospatial Analytics: Experience with GeoPandas, spatial data processing or location-based analytics.
• Software Engineering: Familiarity with Git, Docker, testing, documentation and Agile delivery methodologies.
• Data Visualisation: Ability to create clear dashboards, reports and meaningful visualisations.
• Experience working with IoT, telemetry, sensor-generated data or other high-volume data environments.
• Knowledge of time-series analysis, deep learning, computer vision or generative AI.
• Experience with distributed data processing or NoSQL databases.
• Previous experience taking analytical prototypes through to production.
• Experience validating machine learning outputs and improving model accuracy and reliability.
• Master's degree or equivalent qualification in Data Science, Computer Science, Artificial Intelligence, Mathematics or a related discipline.