CECAN Fellowship: Advanced Data Analysis for Policy Evaluation

data analysis


Mentors: Pete Barbrook-Johnson, Emma Uprichard, Nigel Gilbert


At the core of CECAN’s remit is the aim to pioneer, test and promote innovative evaluation approaches and methods. A key part of this effort is (i) the development of new data analysis techniques and tools, and (ii) improved accessibility and integration of existing techniques and tools. These tools often need to be able to handle large, messy, and incomplete data sets, as organisations conducting and commissioning evaluations often have data sets which fit this description.  These data sets also often require analysis beyond traditional quantitative statistical analysis, to uncover the complex patterns they may contain.


The aim of this fellowship is to allow a researcher or practitioner the time and opportunity to (i) develop novel advanced data analysis tools for evaluators, and/or (ii) bring together existing tools in more accessible forms for evaluators. They will benefit from engaging with the CECAN team and stakeholders to guide their efforts. The tools developed are expected to move beyond traditional statistical approaches.


The fellow is likely to be involved in some or all of the following activities:

  • Development of novel analysis scripts/software and user-interfaces.
  • Interaction with CECAN team members to guide efforts such that the tools/techniques developed are easily applicable to evaluation and the common types of analysis conducted here.
  • Interaction with other evaluation practitioners and commissioners to understand their needs and constraints, and take these into account in efforts.  
  • Dissemination activities aimed at increasing uptake of the developed tools/techniques by evaluation practitioners.
  • Academic dissemination of tools/techniques developed – i.e. journal articles or conference presentations.

This is not an exhaustive list; applicants may wish to propose other activities which complement or extend on the above.

Expertise required:

The applicant should be an experienced data analyst (defined in the broadest sense), with strong expertise either in specific analytical approaches, or in the integration of approaches. The fellow should have experience in working with non-analysts to understand needs and constraints, and have experience in disseminating analysis tools. A background including complexity science and/or Nexus expertise would be a strong advantage.

Format: Funding of up to £10K

Application process: In the first instance you should contact cecan@surrey.ac.uk and the mentors listed above to explore ideas and ensure your application fits with CECAN’s existing work. Please see the CECAN Fellowship Scheme page for more details.


CECAN - funded and supported by the following organisations