At a Glance
- Tasks: Use data science to enhance university reputation and performance through predictive modelling and analysis.
- Company: Join the University of Southampton, a top-ranked, research-intensive institution.
- Benefits: Collaborative environment, professional development, and a chance to impact strategic decisions.
- Other info: Be part of an inclusive team committed to equality and diversity.
- Why this job: Make a real difference in higher education by applying your analytical skills to reputation analytics.
- Qualifications: Strong numeracy, experience with complex datasets, and knowledge of statistical methods required.
The predicted salary is between 54000 - 66000 £ per year.
The University of Southampton is seeking a Data Scientist to join Strategic Planning & Analytics and support work focused on strengthening Southampton’s reputation and performance in external rankings. This new role will help the University build a richer, data-driven understanding of how reputation is formed, measured and influenced.
Working within a dedicated team, you will develop evidence, models and tools that support more effective targeting, prioritisation, decision-making and impact measurement across the University. Your primary focus will be to develop predictive modelling of reputation drivers and outcomes, while also improving the University’s analytical tools, methods and use of data.
You will bring together complex data from a range of internal and external sources, applying appropriate analytical and statistical methods to identify patterns, test assumptions, model potential outcomes and generate actionable insight. You will work with datasets relating to university rankings, reputation indicators, peer and competitor performance, survey outcomes, research and education metrics, and other relevant external and internal sources. This may include data cleaning and transformation, exploratory data analysis, segmentation or clustering, predictive modelling, trend forecasting, scenario modelling, sensitivity analysis, benchmarking and interpretation of composite or weighted indicators.
This is an opportunity to apply data science to work with direct strategic relevance. You will be part of Strategic Planning & Analytics, the University’s central data reporting, insight and analysis team, working in a collaborative analytical environment that brings together expertise in data science, advanced analytics, forecasting, market insight and business intelligence.
We are looking for someone who combines technical analytical capability with excellent judgement, curiosity and communication skills. You will be confident working with complex, incomplete or inconsistent datasets, assessing data quality and limitations, selecting appropriate methods, and translating quantitative analysis into clear insights, options and recommendations for decision-makers. You will need to be comfortable working across organisational boundaries, collaborating with colleagues in professional services and faculties, and communicating technical findings clearly to non-specialist audiences.
Experience of university rankings, league tables, reputation analysis, higher education data or bibliometrics would be valuable, but we are also interested in candidates who can bring strong data science and analytical experience from other relevant contexts.
About You
You will bring:
- Strong numeracy and experience of analysing complex data from multiple sources;
- Knowledge of statistical modelling, predictive analytics, data science or machine learning methods;
- Experience integrating, cleaning, validating and analysing complex datasets;
- The ability to assess data quality, uncertainty, limitations and appropriate use;
- Experience using tools such as Excel, Python, R, SQL, Alteryx or equivalent;
- Experience translating quantitative analysis into clear insight, options and recommendations;
- The ability to communicate technical findings clearly to non-specialist audiences;
- Curiosity, creativity and rigour in using data to solve complex problems;
- Awareness of data protection, data governance and ethical use of data.
Experience of rankings, league tables, reputation surveys, higher education performance metrics, bibliometrics, external datasets such as QS, THE, REF, HESA, NSS, Graduate Outcomes, or data visualisation tools such as Power BI or Tableau would be an advantage.
You will join a supportive and ambitious team within the world-leading, research-intensive University of Southampton, a founding member of the Russell Group and ranked in the top 1% of universities worldwide. You will have the opportunity to apply data science to a high-profile strategic priority, develop expertise in reputation and rankings analytics, and contribute directly to evidence-based decision-making across the University. We are committed to equality, diversity and inclusion and welcome applicants who support our mission of inclusivity.
Data Scientist in Southampton employer: Cyber Security Academy Southampton
As a part-time Cochlear Implant Rehabilitation Specialist at the University of Southampton Auditory Implant Service, you will be joining a supportive and innovative team dedicated to enhancing the lives of cochlear implant users. The role offers flexible working hours, a comprehensive benefits package including a pension scheme, and ample opportunities for professional growth within a collaborative work culture that values your contributions and expertise.
Contact Details:
Cyber Security Academy Southampton Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Southampton
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We think you need these skills to ace Data Scientist in Southampton
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!
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Craft a Tailored Cover Letter:For a full-time role at Cyber Security Academy Southampton, 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 Cyber Security Academy Southampton. 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 Cyber Security Academy Southampton
✨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 Cyber Security Academy Southampton!
✨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.
