Senior Data Scientist

Do you want to help improve the lives of millions of people? Interested in working in the healthtech domain? If you are a driven data professional looking to join a dynamic team that works hard to change the world for the better, we’d love to talk to you.

Role Overview

As a Senior Data Scientist, you will bridge the gap between data science and data engineering. You will develop and maintain the analytical methods, data pipelines, and algorithms that support clinical evidence generation, implanted cardiovascular sensor data analysis, and regulated product development.

In this role, you will translate raw clinical, sensor, and operational data into robust datasets, reproducible analyses, validated algorithms, and clear conclusions for R&D, clinical, quality, regulatory, and software stakeholders.

Key Environment Note: This role requires strong technical skills and the ability to operate within our Quality Management System (QMS) to deliver analysis and software outputs suitable for a regulated medical device environment.

Responsibilities:

• Data Analysis: Analyse complex clinical, physiological, and implanted cardiovascular sensor datasets
• Algorithm & Model Development: Design, implement, test, document, and maintain signal processing methods, statistical modelling, and machine learning models used to interpret system data
• Pipeline Engineering: Create reproducible analysis pipelines and workflows for exploratory analysis, algorithm development, validation, reporting, and regulatory evidence generation
• Cross-Functional Collaboration: Partner with clinical, R&D, software, quality, regulatory, and operations teams to ensure data products and analytical tools meet clinical, product, and business needs
• QMS & Compliance: Support company QMS activities, including requirements, risk assessment, verification, validation, change control, release documentation, and design history file inputs for data and software outputs
• Communication: Clearly communicate analytical methods, assumptions, limitations, results, and conclusions to both internal teams and external stakeholders

Requirements:

• Education: Degree (MSc or PhD preferred) in Data Science, Biomedical Engineering, Statistics, Computer Science, or a related quantitative field
• Experience: Proven experience as a Data Scientist or Data Engineer, ideally within a regulated industry (Medical Devices, Digital Health, or Pharma
• Technical Skills: Strong proficiency in Python/R, machine learning frameworks, signal processing, and building reproducible data pipelines
• Regulatory Knowledge: Experience working under compliance standards is highly desirable