A major Belgian public-sector organisation is expanding its Data Mining team to accelerate strategic data initiatives and turn ad-hoc requests into reusable data products. This Senior Data Scientist will work across advanced machine learning, data modelling and production ML deployment using Python and CI/CD pipelines, and will provide technical leadership, coaching and API/automation experience (FastAPI, Docker). As part of the application you will be asked to submit a short technical exercise explaining how a random forest works and when you would prefer XGBoost or AdaBoost over a random forest.
The mission
The team runs a mix of strategic analytics projects and a continuous intake of operational questions. Current work includes advanced analytics and graph/network analytics pilots, building reproducible ML models for production, and shaping integrations with the data platform. Deliverables target scalable, reusable data products rather than one-off analyses, with an emphasis on reproducibility, documentation and engineering quality.
On a day-to-day basis you will take technical lead on complex data trajectories, shape solutioning and architectural choices, and coach other data scientists and analysts. You will convert incoming requests into prioritized work packages, implement production ML models and APIs, and contribute to team practices such as definition of done, code review standards and CI/CD pipelines. You will coordinate with Data Platform and infrastructure teams to ensure deployments on cloud (AWS/GCP) and infrastructure-as-code (Terraform) meet stability and quality standards.
Your responsibilities
- Lead technical design and delivery of complex analytics projects, ensuring solutions are scalable, reproducible and production-ready
- Coach and uplift the team through code reviews, paired work, knowledge sessions and establishing shared best practices
- Translate and prioritise ad-hoc intake into concrete, reusable data products, templates and datasets that reduce repeat work
- Implement and operate production ML models and APIs, using Python, pandas, scikit-learn and FastAPI, and maintain CI/CD pipelines and Docker-based deployments
- Define and enforce quality standards for documentation, testing, reproducibility and model monitoring
- Support project tracking and stakeholder alignment, maintaining scope, milestones and transparent status reporting
Your profile
Essential skills
- Senior-level experience as a Data Scientist or ML Engineer, strong hands-on proficiency in Python and data modelling with pandas and scikit-learn
- Proven experience deploying production ML models and building APIs (FastAPI), with solid software engineering practices: Git, code reviews, CI/CD pipelines and Docker
- Comfortable with SQL for analytics and data modelling; experience integrating with cloud platforms (AWS or GCP) and Terraform is expected
- Ability to structure ambiguous requests into clear scopes, deliverables and reusable outputs
- Experience coaching/mentoring colleagues and working within Agile/Scrum teams, including facilitation of reviews and technical training
- Strong stakeholder communication skills, able to manage expectations and provide clear progress reports
Languages
- Dutch: C1
- French: C1
- English: C1
Education
- Master in IT or equivalent technical degree with proven professional experience