At a Glance
- Tasks: Analyse complex data to drive research strategy and performance at Durham University.
- Company: Durham University, known for its influential role in higher education.
- Benefits: Competitive salary, professional development, and the chance to shape impactful research initiatives.
- Other info: Collaborative environment with opportunities for career growth and leadership support.
- Why this job: Join a dynamic team and make a real difference in research and innovation.
- Qualifications: Experience in data analysis and a passion for research performance improvement.
The predicted salary is between 37052 - 45286 £ per year.
The purpose of the Strategy, Planning and Insight Department (SPIO) is to work collaboratively to help people to make effective evidence-based decisions and take forward plans and actions aligned to the University’s Strategy. The team has an excellent reputation in the sector for the quality of its work and plays an influential enabling role in relation to the long-term development of Durham University.
The Research Analytics Manager will play a critical role in providing the data insight which is required to advance Durham University’s research strategy, planning and performance. The postholder will join a team of highly skilled planning and analytics professionals in the SPIO team, and will have the opportunity to work closely with colleagues and senior staff across the institution. You will join us at an exciting time as we take forward a new University Strategy and establish impactful research and innovation initiatives at regional, national and global levels.
The Research Analytics Manager will work with complex data sets relating to multiple aspects of research performance, with citations being one key aspect of importance. You will be expected to develop practical ways of enabling insight and understanding; for example, through the development of accessible dashboards, in person dialogue and the facilitation of workshops and other meetings, including those run in partnership with Faculty leadership teams and the University’s bibliometrician.
Specific examples of areas of responsibility include:
- Institution-wide analysis of actionable areas for performance improvement;
- Assessment of citations performance in the context of global rankings;
- Mapping and evaluation of research strengths and opportunities, including interdisciplinary connectivity and generation of grant income;
- Analysis of research reputation and impact;
- Bespoke analysis to inform the identification of potential areas of strategic development.
You will have the opportunity to support the leadership of the Pro-Vice-Chancellor for Research, and to integrate research insights with broader aspects of institutional strategy and development, including staff and financial planning.
Research Analytics Manager employer: Durham University
Durham University is an exceptional employer, offering a collaborative and supportive work culture that fosters professional growth and development. As a Strategic Pre-Award Grants Manager, you will benefit from a dynamic environment that values innovation and teamwork, while also enjoying access to comprehensive training opportunities and a commitment to work-life balance in the vibrant city of Durham.
StudySmarter Expert Advice🤫
We think this is how you could land Research Analytics Manager
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Research Analytics Manager
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 Durham University, 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 Durham University. 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 Durham University
✨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!
✨Showcase Your Projects
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 Durham University!
✨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.
