Data Scientist

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Brussels, Belgique TechNET Temps plein

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pbLocation: Brussels, Belgium – Hybrid role Contract: Initial engagement until March 2027, with potential for 12-month extensions /b /p pWe are working with an established international technology organisation looking to engage an experienced Data Scientist Data Engineer on a contract basis. /p pThis 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. /p pThe successful consultant will take ownership of the full data lifecycle, from exploration and modelling through to validation, automation and production-ready delivery. /p h3Key Responsibilities /h3 ul liAnalyse, clean and transform large, complex datasets from multiple sources. /li liDesign and develop scalable data pipelines using Python and modern data engineering practices. /li liBuild, test and optimise machine learning models, including supervised and unsupervised learning techniques. /li liPerform statistical analysis, time-series modelling, anomaly detection and predictive analytics. /li liWork with geospatial datasets, including spatial processing, mapping and location-based analytics. /li liDevelop automated ETL/ELT workflows and improve data quality, reliability and performance. /li liTransform proof-of-concept models into maintainable, production-ready solutions. /li liUtilise cloud technologies to manage data processing, storage and deployment. /li liDevelop dashboards, visualisations and analytical reports to communicate findings. /li liCollaborate with engineering teams, technical stakeholders and external partners to deliver data-driven solutions. /li /ul h3Technical Requirements /h3 ul liPython: Strong commercial experience with pandas, NumPy, scikit-learn and data processing libraries. /li liData Engineering: Experience developing ETL/ELT pipelines, automating workflows and managing large datasets. /li liMachine Learning: Practical experience with statistical modelling, feature engineering, model evaluation and anomaly detection. /li liSQL: Strong database querying and data manipulation skills. /li liCloud Technologies: Experience working with cloud-based data environments, ideally AWS. /li liGeospatial Analytics: Experience with GeoPandas, spatial data processing or location-based analytics. /li liSoftware Engineering: Familiarity with Git, Docker, testing, documentation and Agile delivery methodologies. /li liData Visualisation: Ability to create clear dashboards, reports and meaningful visualisations. /li liExperience working with IoT, telemetry, sensor-generated data or other high-volume data environments. /li liKnowledge of time-series analysis, deep learning, computer vision or generative AI. /li liExperience with distributed data processing or NoSQL databases. /li liPrevious experience taking analytical prototypes through to production. /li liExperience validating machine learning outputs and improving model accuracy and reliability. /li liMaster's degree or equivalent qualification in Data Science, Computer Science, Artificial Intelligence, Mathematics or a related discipline. /li /ul

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