Data Analyst – Image Capture & Quality

About Scalpel

Medical errors are the third leading cause of death, with many occurring during surgery. Scalpel is on a mission to solve this problem by leveraging cutting-edge computer vision and AI-driven solutions to improve surgical safety.

We are a fast-growing health-tech startup with a dynamic and highly skilled team. Our engineering culture values collaboration, innovation, and problem-solving. As part of our team, you’ll work on real-world challenges that directly impact patient safety worldwide.

Scalpel is seeking a Data Capture Staff to lead the collection, validation, and quality assurance of surgical instrument tray images used to train and evaluate our computer vision models.

You’ll be on the frontline of our AI pipeline, ensuring that the images we capture in hospitals and distributor warehouses are
accurate, consistent, and high-quality

Your work will directly influence the performance of our models and the reliability of our system in real-world surgical environments.

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This role combines hands-on image capture, data quality auditing, and close collaboration with AI engineers to bridge the gap between the surgical logistics and machine learning workflows.

• Capture and curate real-world tray images using Scalpel’s imaging setup
• Perform QA checks on captured images for resolution, lighting, focus, consistency, and completeness
• Collaborate with annotation teams to ensure accuracy and consistency in labelled data
• Maintain structured metadata for captured and annotated datasets
• Work closely with AI engineers to align data collection with model requirements
• Document capture protocols and ensure reproducibility across multiple sites

We’re looking for a detail-oriented, technically strong, and motivated candidate who can combine hands-on data capture with analytical rigour. You should be equally comfortable operating a camera rig in different environments.

Essential Skills & Experience (Must-Have)

• Ability to design and follow structured capture protocols
• Strong attention to detail and ability to spot inconsistencies or errors in large datasets
• Able to demonstrate initiative when dealing with errors, taking ownership of the problem and working with the customer teams where necessary
• Clear written and verbal communication skills to collaborate with engineers and non-technical stakeholders

Why Join Us?

Impact That Matters – Your work directly influences the safety of surgical procedures worldwide

Work on Cutting-Edge AI – Be part of a team working with state-of-the-art computer vision and ML pipelines

Competitive Salary & Benefits – Including a pension scheme and 20 days of holiday + bank holidays

Start-up Energy – Join a fast-moving, mission-driven team with big ambitions and strong backing

How to Apply

Send your CV and a brief cover letter to jobs@scalpel.ai