Biomedical AI Data Scientist: End-to-End ML in Production

HORAIZON; Delft; On-site; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Residence permits and visas

Career growth opportunities

Job summary

HORAIZON Technology BV in Delft, the Netherlands, seeks a Data Scientist who enjoys building end-to-end data solutions. You will own projects, analyze diverse data types, and shape new capabilities in a small team, making a tangible impact.

You should communicate clearly, take initiative, and help others solve problems. The role combines data analysis, backend development with Django and REST APIs, and ML model development across biology-inspired datasets.

Qualifications

• Bachelor’s, Master’s or PhD in a quantitative field is welcome.
• Experience using Python for data analysis and back-end development.
• Experience with ML tools and deploying models to production.

Responsibilities

• Turn scientific and customer needs into practical data solutions.
• Build and improve data pipelines and analytics workflows.
• Automate processing steps for reliability and performance.
• Develop backend services and REST APIs integrate data from multiple systems.
• Work with databases and client-facing web applications.
• Develop and evaluate machine learning models across varied data types.
• Visualise results and explain findings to technical and non-technical audiences.
• Identify improvements and drive delivery.

Skills

Python

Backend development

Machine learning

Communication

Education

Bachelor/Master/PhD in quantitative field

Tools

Django

REST APIs

PyTorch

scikit-learn

Job description

HORAIZON Technology BV in Delft, the Netherlands, seeks a Data Scientist who enjoys building end-to-end data solutions. You will own projects, analyze diverse data types, and shape new capabilities in a small team, making a tangible impact.

You should communicate clearly, take initiative, and help others solve problems. The role combines data analysis, backend development with Django and REST APIs, and ML model development across biology-inspired datasets.