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- Tasks: Support health projects by analysing datasets and creating decision-support tools.
- Company: Leading academic institution focused on innovative health solutions.
- Benefits: Competitive salary, flexible part-time options, and opportunities for impactful work.
- Why this job: Make a difference in public health with your data science skills.
- Qualifications: PhD in a relevant field and strong programming skills in R/Python.
- Other info: Join a collaborative team dedicated to improving health outcomes.
The predicted salary is between 39424 - 43968 £ per year.
A leading academic institution is seeking a highly motivated data scientist to support projects on harmonized health datasets and create public decision-support tools. The role involves developing analysis plans, curating health data, and leading programming in R/Python.
Applicants should have a PhD in a relevant field and strong programming skills.
A salary of £39,424 per annum is offered, with consideration for part-time arrangements. Applications close on 16th February 2026.
Health Data Scientist — Real-World Data & Dashboards in Oxford employer: University of Oxford
Contact Detail:
University of Oxford Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Health Data Scientist — Real-World Data & Dashboards in Oxford
✨Tip Number 1
Network like a pro! Reach out to professionals in the health data science field on LinkedIn or at conferences. We can’t stress enough how valuable personal connections can be in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in R and Python. We all know that actions speak louder than words, so let your work do the talking when you’re in interviews.
✨Tip Number 3
Prepare for those technical interviews! Brush up on your programming skills and be ready to solve problems on the spot. We recommend practicing with real-world datasets to get comfortable with the types of questions you might face.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Health Data Scientist — Real-World Data & Dashboards in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in health data and programming skills. We want to see how your background aligns with the role, so don’t be shy about showcasing your PhD and any projects you've worked on!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about health data and how you can contribute to our projects. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Technical Skills: Since this role involves programming in R/Python, make sure to mention any relevant projects or experiences where you've used these languages. We’re keen to see your technical prowess, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates. Plus, it’s super easy!
How to prepare for a job interview at University of Oxford
✨Know Your Data Inside Out
Make sure you’re well-versed in the health datasets relevant to the role. Brush up on your knowledge of harmonised data and be ready to discuss how you would approach curating and analysing these datasets.
✨Show Off Your Programming Skills
Since programming in R and Python is key for this position, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges beforehand to boost your confidence.
✨Prepare Your Analysis Plans
Think about how you would develop analysis plans for real-world data projects. Be ready to share examples from your past work or hypothetical scenarios that showcase your analytical thinking and problem-solving skills.
✨Engage with Decision-Support Tools
Familiarise yourself with public decision-support tools and be prepared to discuss how you would contribute to their development. Highlight any experience you have in creating dashboards or visualising data to support decision-making.
