Key Responsibilities
Research:
1. This role will enable you to further build your knowledge and experience in exploratory data analysis, inferential statistics, and machine learning, including:
2. Clustering techniques (e.g., k-medoids, hierarchical clustering)
3. Predictive modelling (e.g. Classification and Regression Trees (CART), Linear Regression, Random Forest, Gradient Boosted Models)
4. Natural Language Processing (NLP) with a focus on social listening and topic modelling
5. Integration of generative AI and LLMs in qualitative and survey research processes
6. Inferences about subpopulations (Small Area Estimation (SAE), Multilevel Regression and Poststratification (MRP)
7. You will produce technical reports and sections of high-profile policy reports to be published by NatCen, government departments and agencies, and other clients and partners.
8. You will primarily work with survey data with complex survey weights and administrative data, with the opportunity to also work with social data and GIS data.
9. You will work closely with subject matter experts on policy but will be expected to quickly gain a basic understanding of new policy issues.
10. You will combine advanced data science techniques (machine learning, NLP, data engineering) with robust quantitative research methods (survey analysis, causal inference, MRP) to produce insights that directly inform social policy.
Leadership:
11. You will be joining Britain’s largest independent social research organisation, championing the use of data science to generate insights that help make life better.
12. You will join a growing team, where you will share research approaches, fostering a collaborative and innovative work environment.
13. You will have opportunities to feed into the future direction of data science and analysis at NatCen
Business Development:
14. The role will involve direct contact with clients and collaborators, where you will be advising on analytical methods.
15. You will collaborate with colleagues across specialisms to design research proposals for clients. There is some scope to also pursue and deliver work supported by academic funding.
Skills, Knowledge and Expertise
16. Master's in a relevant field (Data Science, Computer Science, Statistics, etc.) or demonstrated experience through professional development, other learning, or Bachelor’s degree with additional equivalent experience.
17. Experience with practical application of clustering, predictive modelling, and NLP techniques, with familiarity with at least one major machine learning library (eg. Scikit-learn, statsmodels, spaCy, mlr).
18. Proficiency in Python; knowledge of R or SQL is a plus.
19. Familiarity with coding best practices, such as version control, functional code, and documentation
20. Excellent communication, presentation, and report-writing skills.
21. Ability to work collaboratively in a multidisciplinary team.
22. A passion for contributing to policy solutions in areas such as education, employment, equality, social care, crime & justice.
Benefits
As well as a competitive salary, an excellent working environment (including a home/office hybrid working environment), you will be working for the largest independent social research organisation in the UK. We are proud of the benefits we offer our employees which include:
23. 25 days holiday (plus 8 bank holidays) and flexible working
24. Generous company pension scheme
25. Life insurance and health cash plan
26. Cycle to Work scheme and season ticket loan
27. Career development, professional subscriptions support and mentoring support from industry-leading experts.
We are a Disability Confident employer. If you have a disability and wish to apply for this role, please let us know in the application questions below. This allows us to ensure you are considered for an interview if you meet the minimum criteria for the role. If you have any questions or need adjustments at any stage of our recruitment process, feel free to contact us on
*We reserve the right to close this advert before the closing date due to a high volume of applications*