Make Your Mark at Ipsos Do you have expertise in survey research methods and quantitative research principles?
Ipsos is recruiting a Quantitative Research Manager to work within our Probability Surveys Unit (PSU). The PSU designs and manages some of the largest and most technically complex government studies.
This is an exciting opportunity for a quantitative researcher skilled in survey methodology, sampling and weighting. We are seeking someone with Knowledge of sampling and/or weighting approaches used in social, public affairs, market or academic research and experience working with large datasets and using SPSS, R, Stata or similar statistical software.
What is in it for you? You will get the opportunity to:
- Play a key role in designing and deliver high-quality random probability work through our online probability panel the KnowledgePanel as well as ad-hoc research.
- Contribute to the design, implementation and continuous improvement of survey methodologies
- Challenge existing processes and seek to develop innovative improvements.
- Get exposure to the entire breath of Ipsos policy research, from politics, to public services, employment and welfare, transport, climate change and energy, societal attitudes and many more.
- Working with the UK KnowledgePanel, Ipsos's online random probability panel, to create sampling frames and draw random probability samples to maintain nationally representative samples.
- Supporting our Probability Surveys Unit to deliver large, complex probability surveys through sampling, weighting and methodological innovation.
- Collating and managing population data from official ONS statistics and other large scale probability surveys to support weighting methods.
- Writing clear and concise technical reports, documenting your activities, setting out objectives, challenges and solutions.
- Explaining complex methods clearly to clients and other non-technical colleagues.
- Work with junior staff to help develop their methodological and statistical skills.
- Lead and contribute to innovation work, keeping abreast of new relevant developments and aiming to continually improve processes and quality
- Contributing to the design of experimental approaches to deliver methodological innovations and efficiencies.
- You will use Ipsos' in-house AI to support your work and help to develop AI agentic solutions.
- You will be supported by experienced staff who will provide support and guidance.
- Strong understanding of survey research methods and quantitative research principles.
- Knowledge of sampling and/or weighting approaches used in social, public affairs, market or academic research.
- Experience working with large datasets and using SPSS, R, Stata or similar statistical software.
- Strong statistical aptitude and confidence working with quantitative data.
- Strong organisational skills and ability to manage multiple priorities simultaneously, while maintaining accuracy and attention to detail.
- Excellent written and verbal communication skills, including the ability to explain technical concepts to non-technical audiences.
- Degree-level qualification or above in a quantitative discipline such as Statistics, Social Research Methods, Mathematics, Economics, Psychology, Data Science or a related subject, or equivalent relevant experience.
- Experience designing or implementing survey samples for probability-based or random probability studies.
- Experience developing, applying or evaluating survey weights.
- Understanding of survey error, non-response bias, coverage error and weighting adjustment techniques.
- Experience working with online panels, longitudinal studies or official statistics.
- Experience of process automation, reproducible workflows, scripting or systems development.
- Experience developing technical documentation, methodological reports or survey standards.
- Experience contributing methodological expertise to proposals, bids or client presentations.
- Knowledge of multivariate statistical techniques and survey data analysis e.g. factor analysis, clustering, regressions, multilevel models.
Vacancy posted 7 days ago
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