Clinical Scientist

About this role

Your responsibilities:

• Get authorised to assess the clinical evaluation processes of innovative medical devices, focusing on clinical studies and clinical evidence
• Collaborate with a multidisciplinary team on technical documentation assessments
• Create content on clinical AI, biostatistics, clinical research methodology, and real-world evidence to educate teammates, customers and prospects
• Represent Scarlet externally at events and conferences
• Screen and action regulatory insights from the latest research, standards and guidance
• Support Sales and Customer Experience by providing regulatory and scientific insights on prospects and customers
• Work with Product, Engineering, Design and Applied ML teams to build and improve systems
• Support Technical Operations as they expand Scarlet’s approvals in various jurisdictions and technologies

The key skills:

• Education: Degree in clinical medicine, nursing, dentistry, epidemiology or public health
• Minimum two years experience assessing clinical data for medical devices
• Experience developing, implementing or evaluating medical device software
• Knowledge of principles for assessment of clinical data and medical statistics
• Minimum two years experience in patient care
• Practical experience conducting or monitoring clinical investigations/trials or assessing clinical data

Desirable skills:

• Ferociously curious — comfortable exploring complex topics and challenging the status quo
• Excellent communicator — strong written and verbal communication skills
• Highly adaptable — able to operate autonomously in ambiguous situations
• Guidance knowledge — familiarity with standards and guidance used for clinical evaluation (e.g. ISO 14155, MEDDEV 2-7/1 Rev.4)
• Research savvy — knowledge of clinical research methodologies and experience designing or contributing to interventional and non-interventional studies
• Biostatistics expert — experience applying biostatistical methods in clinical research or critically appraising statistical methodologies
• AI fluent — strong technical knowledge of modern generative AI (LLMs, embeddings, RAG, fine-tuning, evaluation/monitoring) and understanding of limitations and failure modes

The interview process

• 1. Intro call with Sandy — 30 mins
• 2. Interview with member of Devices function and Sandy — 2x30 mins
• 3. Technical interview with Camille — 1 hour
• 4. Culture and values interview with James and Jamie — 2x30 mins
• 5. Referencing & offer