You will:

• Support the data science workflow for specific projects, from problem framing to delivery.

• Analyse proprietary biomedical datasets to identify patterns, variability, and opportunities for improved performance.

• Help develop and apply statistical and machine learning methods for noisy, high-dimensional, and often small-sample data.

• Contribute to validation strategies, including uncertainty and robustness checks.

• Help improve preprocessing pipelines, signal quality, and acquisition protocols through work with raw data and instrumentation.

• Apply chemometric and multivariate analysis to spectroscopic data.

• Work cross-functionally with experimental, hardware, and product teams.

• Communicate findings, trade-offs, and recommendations clearly to technical and non-technical stakeholders.

• Contribute to reusable ...