Principal Data Scientist

Overview

In this role you will act as a subject-matter expert in biomedical signal analysis, probabilistic modelling and scalable data pipelines to generate high-quality insights from complex high-frequency data. You will work embedded with a pharmaceutical client, driving clinically relevant analyses and maintaining quality and reproducibility. You will tackle signal processing, ML model development, and data integration to support clinical studies and health research. This is an opportunity to shape analytics for next-generation patient treatment with autonomy and cross-functional collaboration.

Responsibilities

• Identify, access and integrate diverse data sources from clinical studies, observational data and real-world healthcare datasets
• Develop and implement signal processing methods for feature extraction from high-frequency data
• Build and validate machine learning models for clinical applications including disease phenotyping and prediction
• Apply time-series, longitudinal and probabilistic modelling to enhance biomedical interpretation
• Maintain scalable, high-performance data pipelines aligned with business needs and best practices
• Benchmark models against state-of-the-art methods ensuring clinical relevance and interoperability

Key requirements

• PhD/Masters or Bachelor’s degree in computer science, biomedical engineering, mathematics, data science or related discipline
• Experience in pharma or healthcare industry
• Strong written and verbal communication, ability to write technical reports and concise summaries
• Expertise in advanced analytical techniques including ML and signal processing for physiological data
• Proficiency in R or Python with hands-on ML and data analysis experience
• Experience with data extraction and integration techniques including APIs, relational databases, cloud-based solutions
• Software engineering best practices for version control, code reviews, and testing
• Proficient with cloud technologies (e.g., AWS)
• Experience handling diverse healthcare data formats (EHR, electrophysiological signals, wearable data) and adherence to GxP/regulatory guidance

• Strong communication skills
• Analytical thinking and problem-solving
• Ability to work autonomously within a client-embedded program
• Signal processing for biomedical data
• Probabilistic modelling
• Time-series and longitudinal analysis

…