Data Scientist
Solliciteren
Plaats
Brussel1000
Brussel
België
Contract
Vooltijds, Onbepaalde duurDatum gepubliceerd
2026-02-18Online to:
2026-04-19EUR 20.00 HOUR
Data Scientist
- EMS Health
- Brussel
- 10 uren geleden
As a Data Scientist at EMS Health, your mission is to unlock the full potential of healthcare data to support operational decision-making and product innovation. You will contribute hands-on to the evolution of our AI products, with a strong focus on experimentation, evaluation, and pragmatic delivery. The role combines applied ML, data preparation, and model evaluation, with increasing exposure to modern architectures and LLMs used in production-grade workflows.
Key objectives:
Help identify high-impact use cases where data science can bring measurable value to our internal processes, clients, and partners.
Contribute to data science initiatives supporting our clinical AI products and long-term innovation.
Help develop a realistic and agile R&D plan that balances short-term deliverables with long-term research goals.
Ensure that all models and analytical tools are developed with scalability, interpretability, and clinical relevance in mind.
Collaborate with cross-functional teams to translate business needs into data-driven solutions.
Responsibilities
Design, train & improve ML models for clinical NLP tasks ( e.g., entity recognition, relation extraction, and entity linking)
Analyze structured and unstructured healthcare data to identify trends, anomalies, and opportunities for improvement.
Prepare, clean, and maintain training and evaluation datasets, including re-annotation and quality control.
Build and maintain robust evaluation frameworks (offline & client facing) to ensure performance & non-regression
Integrate LLMs in clinical AI workflows for validation, annotation & RAG pipelines
Help productionize LLM-based tools through fine-tuning, distillation & quantization to meet latency and cost constraints
Contribute to the automation of manual tasks in cross-functional teams
Qualifications
Master's degree in Data Science, Computer Science, Statistics, or a related field.
Prior experience in data science, applied NLP, or ML role.
Strong knowledge of Python and common ML libraries (e.g., PyTorch, Hugging Face, vLLMs) and good working knowledge of git, Linux
Experience working with real-world data, ideally in healthcare or life sciences ;
Hands-on attitude with analytical mindset & strong problem-solving skills, focused on Agile methodology and lean management ;
Comfortable working both independently and in a collaborative team environment.
Fluent in English and also either French or Dutch ;
Bonus points for:
Experience with terminology mapping or medical data.
Familiarity with workflow orchestration tools (e.g., Prefect, Airflow).
Knowledge of data versioning (e.g., DVC)
Key objectives:
Help identify high-impact use cases where data science can bring measurable value to our internal processes, clients, and partners.
Contribute to data science initiatives supporting our clinical AI products and long-term innovation.
Help develop a realistic and agile R&D plan that balances short-term deliverables with long-term research goals.
Ensure that all models and analytical tools are developed with scalability, interpretability, and clinical relevance in mind.
Collaborate with cross-functional teams to translate business needs into data-driven solutions.
Responsibilities
Design, train & improve ML models for clinical NLP tasks ( e.g., entity recognition, relation extraction, and entity linking)
Analyze structured and unstructured healthcare data to identify trends, anomalies, and opportunities for improvement.
Prepare, clean, and maintain training and evaluation datasets, including re-annotation and quality control.
Build and maintain robust evaluation frameworks (offline & client facing) to ensure performance & non-regression
Integrate LLMs in clinical AI workflows for validation, annotation & RAG pipelines
Help productionize LLM-based tools through fine-tuning, distillation & quantization to meet latency and cost constraints
Contribute to the automation of manual tasks in cross-functional teams
Qualifications
Master's degree in Data Science, Computer Science, Statistics, or a related field.
Prior experience in data science, applied NLP, or ML role.
Strong knowledge of Python and common ML libraries (e.g., PyTorch, Hugging Face, vLLMs) and good working knowledge of git, Linux
Experience working with real-world data, ideally in healthcare or life sciences ;
Hands-on attitude with analytical mindset & strong problem-solving skills, focused on Agile methodology and lean management ;
Comfortable working both independently and in a collaborative team environment.
Fluent in English and also either French or Dutch ;
Bonus points for:
Experience with terminology mapping or medical data.
Familiarity with workflow orchestration tools (e.g., Prefect, Airflow).
Knowledge of data versioning (e.g., DVC)