Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead a team to develop AI/ML models for early cancer detection.
- Company: Join a pioneering healthtech company transforming diagnostics and clinical innovation.
- Benefits: Enjoy a hybrid work model and contribute to impactful healthcare solutions.
- Why this job: Shape the future of medical AI while making a difference in patient outcomes.
- Qualifications: Advanced degree in relevant fields and experience in healthcare AI/ML projects required.
- Other info: Ideal for those passionate about data-driven healthcare innovations.
The predicted salary is between 43200 - 72000 £ per year.
We are partnering with a pioneering healthtech company at the intersection of advanced diagnostics, data science, and clinical innovation. This UK-based leadership role will shape AI and machine learning strategy for early cancer detection, helping transform how we identify disease at its most treatable stage.
Responsibilities
- Lead a growing team of data scientists developing ML/AI models for real-world clinical data
- Own the end-to-end lifecycle of AI/ML projects — from data acquisition to deployment
- Collaborate with lab, regulatory, and product teams to align on technical and clinical priorities
- Champion innovation in medical AI, staying current with emerging tools, frameworks, and methodologies
- Ensure model quality and regulatory readiness in compliance with medical device standards
Qualifications
- Advanced degree or equivalent experience in computer science, bioinformatics, engineering, or related field
- Proven experience leading AI/ML projects in healthcare, life sciences, or diagnostics
- Strong background in Python and common machine learning toolchains (e.g. MLflow, PyTest, GitHub)
- Excellent communication skills for cross-functional collaboration and regulatory documentation
- Based in the UK with the ability to work in a hybrid model; experience with QMS or regulated environments (e.g. ISO13485) is a plus
This is a high-impact role in a mission-driven company where data science directly supports patient outcomes. If you’re passionate about translating complex data into life-saving insights, we’d love to hear from you.
Contact Detail:
LinkedIn Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager, Oncology Diagnostics - Scotland
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly in the context of oncology diagnostics. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the healthtech and data science fields. Attend relevant conferences or webinars to connect with industry leaders and gain insights into current trends and challenges in cancer detection.
✨Tip Number 3
Prepare to discuss your leadership style and experiences in managing AI/ML projects. Be ready to share specific examples of how you've successfully led teams and delivered impactful results in a healthcare setting.
✨Tip Number 4
Stay updated on regulatory standards related to medical devices, especially ISO13485. Understanding these regulations will demonstrate your commitment to quality and compliance, which is crucial for this role.
We think you need these skills to ace Data Science Manager, Oncology Diagnostics - Scotland
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI/ML projects, particularly in healthcare or diagnostics. Emphasise your leadership skills and any specific tools or methodologies you've used that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for oncology diagnostics and how your background makes you a perfect fit for this role. Mention specific projects or achievements that demonstrate your ability to lead a team and drive innovation in medical AI.
Showcase Technical Skills: Clearly outline your proficiency in Python and any machine learning toolchains mentioned in the job description. Provide examples of how you've applied these skills in previous roles, especially in regulated environments.
Highlight Communication Abilities: Since excellent communication is crucial for this role, include examples of how you've successfully collaborated with cross-functional teams. Discuss any experiences where you had to document regulatory compliance or present complex data insights to non-technical stakeholders.
How to prepare for a job interview at LinkedIn
✨Showcase Your Leadership Experience
As a Data Science Manager, you'll be leading a team. Be prepared to discuss your previous leadership roles, how you managed teams, and the impact of your leadership on project outcomes.
✨Demonstrate Technical Proficiency
Make sure to highlight your experience with Python and machine learning toolchains. Be ready to discuss specific projects where you've used these skills, especially in healthcare or diagnostics.
✨Understand the Regulatory Landscape
Familiarise yourself with medical device standards and regulations like ISO13485. Being able to speak knowledgeably about compliance will show that you understand the importance of quality and safety in healthcare.
✨Communicate Effectively
Excellent communication is key for this role. Prepare examples of how you've successfully collaborated with cross-functional teams and how you’ve documented technical processes for regulatory purposes.
