Our client

Our client is a fast-growing medtech start-up redefining how biomarker intelligence and data science accelerate clinical decision-making. Fresh from our Series B funding, they’re scaling their data-driven platform that bridges biology, AI, and engineering to bring precision diagnostics closer to patients.

Their work sits at the intersection of biotech, data, and digital health—and they’re building a team passionate about translating complex biological signals into meaningful clinical insights.

The Role

We’re looking to hire a Data Scientist with a strong foundation in biomedical data analysis and experience working in fast-paced, cross-disciplinary environments. You’ll help design and implement analytical models that extract insights from biomarker data, clinical studies, and device signals.

You’ll collaborate closely with researchers, software engineers, the CTO and the Head of Product to translate raw data into actionable discoveries that drive the product roadmap.

Key Responsibilities

• Design and implement statistical and machine learning models to interpret biomarker and clinical data;
• Work with Research & Engineering to define data requirements and ensure data quality;
• Analyze multimodal datasets (e.g., omics, biosensor, or imaging data);
• Contribute to data pipelines and workflows for reproducible research using Python, R, and cloud-based tools (Nextcloud, GCP and AWS);
• Communicate findings clearly to technical and non-technical stakeholders;
• Collaborate on publications, regulatory submissions, and clinical validations.

Requirements

• MSc or PhD in Data Science, Bioinformatics, Biostatistics, Computational Biology, or related field;
• Over three years of experience as a data scientist, ideally in biotech, medtech, or life sciences;
• Strong experience with Python (pandas, scikit-learn, NumPy) or R, and solid understanding of statistics and machine learning;
• Experience working with cloud environments—Nextcloud, GCP, or AWS;
• Comfortable in a start-up or scale-up environment, with a hands-on, agile mindset;
• Familiarity with data governance, privacy standards (GDPR), and clinical research protocols;
• Excellent communication and collaboration skills.