Job Title: Data Scientist
Language: English, French, and English
Location: 1000 Brussels, Belgium
Duration: 22/06/2026 - 31/12/2026
Job Description:
The Data mining team is looking for a senior profile who will complete a double assignment:
* Accelerate strategic data initiatives through substantive expertise, technical direction and coaching.
* Control the continuous flow of ad-hoc data questions through overview, prioritization, bundling and translation into reusable solutions/data products.
The role brings seniority, structure and technical depth to the Data mining team, and at the same time supports the operation and follow-up together with, among others, the team leader and other stakeholders.
Core responsibilities :
Strategic projects & technical leadership
* Include the technical lead in complex data processes (e.g. advanced analytics, graph/network analytics, integrations, architectural choices).
* Helping to shape the approach, solutioning and priorities of larger initiatives, with an eye for feasibility, impact and scalability.
* Monitoring and propagating quality standards, including reproducibility, documentation, methodology and – where relevant – engineering quality.
Team uplift & co-creatie (binnen Data mining)
* Coaching and guiding data scientists and analysts through co-creation, substantive reviews and sharing best practices.
* Structurally contribute to the increase of team competencies (methodology, approach, quality, communication).
* Taking an active role in the development of team agreements, such as definition of done, working methods and knowledge sharing.
Structure and productize ad-hoc demand flow
* Creating an overview of incoming questions: intake, slicing, prioritization, status/communication.
* Cluster ad-hoc work and, where possible, convert it into structural, reusable solutions (reusable datasets, analysis methods, templates, data products).
* Apply FAIR principles from a data product point of view with a focus on reusability and quality.
Project management & follow-up (Stretch)
* Include basic delivery/project follow-up (scope, milestones, dependencies, risks).
* Supporting the team leader in follow-up and coordination to bring stability to planning and execution.
* Contributing to stakeholder alignment, including expectation management, decision-making and (where necessary) escalations.
Collaboration & stakeholders:
* Working closely within the Data mining team (data scientists/analysts, and where relevant data engineers/platform stakeholders).
* Collaboration with Data Platform team and substantive partners/stakeholders.
* Works in an environment with multiple priorities, where there is a need for structure in intake, follow-up and communication.
Profile (must-haves) :
* Master in IT
* Strong, hands-on experience as a Data Scientist / ML Engineer with a focus on Python.
* Experience with data analysis and modeling (pandas, scikit-learn) and building/improving ML models in a production context.
* Strong software engineering foundation: Git, code reviews, CI/CD pipelines, Docker; experience in setting up APIs and reusable components (e.g. FastAPI).
* Knowledge of SQL; experience with infrastructure-as-code or cloud is a plus (Terraform, AWS/GCP).
* Strong in structuring unclear questions and translating them into concrete approaches/deliveries
* Experience with coaching/mentoring and working in co-creation (e.g. technical training, reviews, SCRUM/scrum master role).
* Strong communication skills (involving stakeholders, clear reporting, managing expectations).
* Trilingualism (NL/FR/EN) strongly desired and preferably at a high level.
Pluspunten (nice-to-haves) :
* Experience with data product thinking, governance and quality principles (FAIR, definitions, documentation, reusability).
* Ervaring met graph analytics / network analytics of andere advanced analytics domeinen.
* Knowledge of Databricks.
* Previous experience within an OISZ is a big plus.
* Previous experience with secondary data use and fraud detection.
Customer Information
Customer - Project Information
Expected impact (3–6 months) :
* Clearer intake and prioritization process for ad-hoc queries to the Data mining team.
* More reusable and scalable outputs instead of one-offs.
* Measurable uplift in team quality through coaching, reviews and methodical agreements.
* Better predictability and progress on key data journeys and strategic initiatives.
Skills
* Agile / Scrum
* AI & Machine learning
* API
* AWS
* CI/CD pipelines
* Data analysis
* Data modeling
* Docker
* GCP
* GIT
* Java
* ML
* Pandas
* Python
* SQL
* Terraform