Clinical Evidence Specialist

Our mission is to hasten the transition to universally accessible healthcare. We are authorised by governments to assess and grant market access to medical AIs. Our groundbreaking approach enables the most innovative technology to reach patients safely and quickly.

Scarlet is the pre-eminent authority on AI medical devices. We serve customers that matter. Companies building bleeding-edge medical AI systems choose Scarlet. We are proud to count the world’s best resourced and most ambitious companies building medical AI as customers. You will be joining a team with product-market fit, flowing data, and exponentially growing revenue.

Come help us bring the next generation of healthcare to the people who need it.

ABOUT THIS ROLE

Scarlet’s Devices function is a team of clinicians, AI experts, and software engineers, working together to assess and certify the most innovative and impactful medical device software.

We pride ourselves on delivering fast and efficient assessments to enable market access, new device updates and ongoing surveillance of a growing portfolio of medical devices.

As we continue to scale our activities and certify more and more medical devices, we need biostatistics and clinical evidence expertise to provide support across all stages of the customer journey.

You'll scrutinise the clinical evidence submitted by manufacturers of AI-enabled and software medical devices — evaluating study design, statistical methodology, validity of conclusions and real-world evidence to determine whether it supports the claimed intended purpose.

YOUR RESPONSIBILITIES

• Get authorised to contribute to the clinical evaluation processes of the most innovative medical devices in the world, focussing on clinical studies and clinical evidence
• Collaborate with a multidisciplinary team on technical documentation assessments
• Create content in areas like biostatistics, clinical research methodology, and real world evidence to educate teammates, customers and prospects
• Deploy your expertise externally by representing Scarlet at events and conferences
• Screen and action regulatory insights from the latest research, standards and guidance
• Support the Sales and Customer Experience function by providing regulatory and scientific insights on prospects and customers
• Work with our Product, Engineering, Design and Applied ML functions to build and improve our systems

THE KEY SKILLS

• Education - A degree in medical statistics, biostatistics, epidemiology, or similar
• Work experience - Experience either in the hands-on application of biostatistical methods in clinical research, or in the critical appraisal of statistical methodologies used in clinical studies and scientific literature
• Work experience - Experience appraising or analysing real-world data and observational studies, including familiarity with bias frameworks (e.g. ROBINS-I, GRADE for observational evidence)
• Work experience - Working understanding of how AI/ML models are developed, validated, and evaluated in clinical contexts (e.g. TRIPOD-AI, DECIDE-AI, dataset shift, performance generalisation).
• Work experience - Practical experience in conducting or monitoring clinical investigations/trials or assessing clinical data [NBOG - clin eval]

DESIRABLE SKILLS

• Ferociously curious - You like going down rabbit holes, understanding deeply how things work, and challenging the status quo
• Problem-solver - You can identify and define scientific problems, defend a scientific position and ideate pragmatic solutions
• Excellent communicator - You have exceptional written & verbal communication skills
• Highly adaptable - You have worked in different environments and like operating with autonomy on sometimes ambiguous tasks
• Guidance knowledge - You have knowledge or training in the relevant standards and guidance used for clinical evaluation (e.g. ISO 14155, MEDDEV 2-7/1 Rev.4)
• Research savvy - You have knowledge of different clinical research methodologies, including experience designing or contributing to the development of interventional and non-interventional clinical studies

THE INTERVIEW PROCESS

• Intro call with Sandy https://www.linkedin.com/in/wrightsandy/ - 30 mins
• Interview with Yun https://www.linkedin.com/in/yun-hsuan-chang-2b8a53138/ - 30 mins
• Technical interview with Mihir https://www.linkedin.com/in/dr-mihir-kelshiker-39968b57/ - 1 hour
• Culture and values interview with James https://www.linkedin.com/in/james-dewar-78758992/?originalSubdomain=uk and Jamie https://www.linkedin.com/in/jamie-cox-01458b3a/?originalSubdomain=uk - 2x30 mins
• Referencing & offer