Ph3Senior Data Scientist / Technical Lead /h3 h3Role Overview /h3 pWe 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. /p h3Key Responsibilities /h3 h3Technical Leadership Strategic Initiatives /h3 ul liLead complex data science and machine learning projects from design to production. /li liDrive architectural and technical decisions for advanced analytics initiatives. /li liDefine and promote best practices for reproducibility, documentation, code quality, and data science methodologies. /li liSupport the development of scalable and maintainable data products. /li /ul h3Team Coaching Knowledge Sharing /h3 ul liMentor data scientists and analysts through code reviews, technical coaching, and collaborative problem‑solving. /li liImprove team capabilities in analytics, machine learning, software engineering, and delivery practices. /li liContribute to team processes, standards, and knowledge‑sharing initiatives. /li /ul h3Data Products Analytics Delivery /h3 ul liStructure, prioritize, and manage incoming analytical requests. /li liTransform one‑off analyses into reusable datasets, models, templates, and data products. /li liApply data governance and FAIR principles to improve data quality, accessibility, and reusability. /li liDevelop and maintain machine learning solutions in production environments. /li /ul h3Stakeholder Project Coordination /h3 ul liCollaborate with business stakeholders, data engineers, platform teams, and management. /li liSupport planning, risk management, prioritization, and delivery tracking. /li liCommunicate technical concepts clearly to both technical and non‑technical audiences. /li /ul h3Required Skills Experience /h3 ul liMaster's degree in Computer Science, Data Science, Engineering, or a related field. /li liStrong hands‑on experience as a Data Scientist or ML Engineer. /li liAdvanced Python expertise, including Pandas, Scikit‑learn, and machine learning frameworks. /li liExperience developing, deploying, and maintaining production‑grade ML models. /li liStrong software engineering background with Git, CI/CD, Docker, APIs, and reusable service architectures (e.g., FastAPI). /li liSolid SQL skills and experience with data modeling and data analysis. /li liExperience with Agile/Scrum methodologies and mentoring technical teams. /li liExcellent analytical, communication, and stakeholder management skills. /li /ul h3Nice to Have /h3 ul liExperience with Databricks. /li liKnowledge of graph analytics, network analytics, or advanced analytics techniques. /li liExperience with AWS, GCP, Terraform, and cloud‑native architectures. /li liKnowledge of data product management, governance, and FAIR principles. /li liExperience in fraud detection, secondary data use, or highly regulated environments. /li /ul h3Languages /h3 ul liDutch, French, and English (professional working proficiency preferred). /li /ul h3Work Environment /h3 ul liHybrid working model. /li liLocation: Brussels, Belgium. /li liCollaboration with multidisciplinary data, analytics, and platform teams. /li /ul h3Candidate Assessment /h3 pCandidates 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. /p /p #J-18808-Ljbffr