Data Scientist Dunfermline

Permanent

ABOUT US

When a five-year-old boy was blinded after a regular eye exam failed to spot a retinal detachment, his father made it his life’s work to help eye care professionals by revolutionising retinal imaging. Optos was founded by Douglas Anderson in 1992 with the goal to make a patient-friendly device to quickly capture the entire retina.

The experience of Douglas Anderson is a thread that runs through the company to this day and has resulted in our products being used in nearly 20,000 locations globally. Optomap® shows up to 82% (200°) of the retina in a single-capture, offering unrivalled clarity and Optos is proud to be recognised as the leader in this field.

ROLE SUMMARY

We are seeking a talented Data Scientist to join our Research and Development department, based in Dunfermline. In this role, you will develop, optimise and evaluate machine learning models and computer vision algorithms for retinal imaging, ensuring they are successfully integrated into our products. Collaborating with cross-functional teams, you will support model deployment, verification and ongoing performance assessment, driving continuous improvements to product quality, accuracy and user value.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Develop, evaluate and deliver robust machine learning models and analytical methods for retinal imaging applications, ensuring all solutions are thoroughly documented and suitable for product development and clinical research environments.
• Produce clear and comprehensive technical reports, including model performance evaluations, experimental designs and results, to support product development, verification activities and commercial decision-making.
• Collaborate closely with Product Management, Clinical and other internal stakeholders to ensure machine learning solutions meet defined product requirements, performance standards and business objectives.
• Support the successful commercialisation of machine learning technologies by contributing to product integration, verification, validation and deployment activities.
• Work with clinical research partners and healthcare stakeholders to evaluate the clinical effectiveness and diagnostic performance of machine learning models and analytical methods.
• Contribute to the development, implementation and continuous improvement of processes, methodologies, standards and infrastructure that support machine learning and data science activities.
• Build and maintain effective relationships with external research and technology partners, including universities and commercial organisations, facilitating the transfer of knowledge, data assets, algorithms, prototypes and best practices into the business.
• Identify and explore opportunities to apply data science and analytics to improve business performance, customer outcomes and operational efficiency.
• Stay up to date with emerging research, technological advancements, industry standards and regulatory requirements relevant to machine learning, artificial intelligence and medical imaging.
• Share expertise and insights across the organisation, helping to foster innovation and promote best practices in machine learning and data science.