Job Description
Senior Data Scientist / Technical Lead
We are seeking a Senior Data Scientist to provide technical leadership, coaching, and strategic direction within a Data Mining team. The role combines hands-on advanced analytics and machine learning expertise with stakeholder management, team mentoring, and the transformation of ad-hoc analytical requests into scalable data products and reusable solutions.
Key Responsibilities
Technical Leadership & Strategic Initiatives
- Lead complex data science and machine learning projects from design to production.
- Drive architectural and technical decisions for advanced analytics initiatives.
- Define and promote best practices for reproducibility, documentation, code quality, and data science methodologies.
- Support the development of scalable and maintainable data products.
Team Coaching & Knowledge Sharing
- Mentor data scientists and analysts through code reviews, technical coaching, and collaborative problem-solving.
- Improve team capabilities in analytics, machine learning, software engineering, and delivery practices.
- Contribute to team processes, standards, and knowledge-sharing initiatives.
Data Products & Analytics Delivery
- Structure, prioritize, and manage incoming analytical requests.
- Transform one-off analyses into reusable datasets, models, templates, and data products.
- Apply data governance and FAIR principles to improve data quality, accessibility, and reusability.
- Develop and maintain machine learning solutions in production environments.
Stakeholder & Project Coordination
- Collaborate with business stakeholders, data engineers, platform teams, and management.
- Support planning, risk management, prioritization, and delivery tracking.
- Communicate technical concepts clearly to both technical and non-technical audiences.
Required Skills & Experience
- Master's degree in Computer Science, Data Science, Engineering, or a related field.
- Strong hands-on experience as a Data Scientist or ML Engineer.
- Advanced Python expertise, including Pandas, Scikit-learn, and machine learning frameworks.
- Experience developing, deploying, and maintaining production-grade ML models.
- Strong software engineering background with Git, CI/CD, Docker, APIs, and reusable service architectures (e.g., FastAPI).
- Solid SQL skills and experience with data modeling and data analysis.
- Experience with Agile/Scrum methodologies and mentoring technical teams.
- Excellent analytical, communication, and stakeholder management skills.
Nice to Have
- Experience with Databricks.
- Knowledge of graph analytics, network analytics, or advanced analytics techniques.
- Experience with AWS, GCP, Terraform, and cloud-native architectures.
- Knowledge of data product management, governance, and FAIR principles.
- Experience in fraud detection, secondary data use, or highly regulated environments.
Languages
- Dutch, French, and English (professional working proficiency preferred).
Work Environment
- Hybrid working model.
- Location: Brussels, Belgium.
- Collaboration with multidisciplinary data, analytics, and platform teams.
Candidate Assessment
Candidates may be required to complete a technical exercise demonstrating their understanding of machine learning concepts and model selection approaches, including ensemble learning techniques such as Random Forest, XGBoost, and AdaBoost.
