At a Glance
- Tasks: Lead research in health economics and epidemiology using large healthcare datasets.
- Company: Join the prestigious University of Oxford's Nuffield Department.
- Benefits: Enjoy 38 days annual leave, hybrid working, and a great pension scheme.
- Other info: Dynamic research environment with opportunities for professional growth.
- Why this job: Make a real impact in healthcare research while developing your skills.
- Qualifications: Postgraduate degree in health economics or related field; strong R programming skills.
The predicted salary is between 39424 - 47779 £ per year.
The postholder will lead the development of analysis plans and conduct high‑quality research in health economics, epidemiology, and real‑world evidence using large observational healthcare datasets. They will provide written technical input into protocols and ethics committee submissions, contribute to study protocol and analysis plan development, and manage data cleaning, analysis, and report writing.
Responsibilities include maintaining data integrity, carrying out reproducible analytical workflows in R, and disseminating findings through peer‑reviewed publications, conference presentations, and other scientific communications.
You hold a postgraduate degree in health economics, epidemiology, applied medical statistics or a closely related field. You have experience with health‑economics and epidemiological methods in observational research, strong programming skills (preferably in R), and a proven record of research reports and peer‑reviewed publications appropriate to your career stage. A PhD/DPhil in Health Economics, Epidemiology, Medical Statistics, or a comparable discipline and experience with UK healthcare datasets such as CPRD or HES is desirable.
What We Offer:
- Excellent contributory pension scheme
- 38 days annual leave
- Comprehensive range of childcare services
- Family leave schemes
- Discounted bus travel and season‑ticket travel loans
- Membership to a variety of social and sports clubs
- Hybrid working options
The University of Oxford is committed to equality and valuing diversity. All applicants will be judged on merit according to the selection criteria. Applications should be made online and must include a CV and a supporting statement explaining how the applicant meets the selection criteria, with examples of skills and experience. The closing date for applications is Wednesday, 22 July 2026. Interviews will take place during the week commencing 24 August 2026 and will be online. Please quote reference 187413 in all correspondence.
Data Scientist in Health Economics and Epidemiology employer: Corehr
Sheffield Hallam University is an exceptional employer, offering a vibrant and inclusive work culture that fosters innovation and collaboration within the Smart Interactive Technologies Lab. As a Research Fellow, you will have access to cutting-edge research infrastructure and the opportunity to contribute to impactful projects aimed at improving maternal health outcomes, all while benefiting from a supportive environment that prioritises professional growth and development. Join us in making a meaningful difference in healthcare through responsible and human-centred digital innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Health Economics and Epidemiology
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We think you need these skills to ace Data Scientist in Health Economics and Epidemiology
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Corehr, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Corehr. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Corehr
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Corehr!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
