Research Assistant in Tax Analysis at London School of Economics and Political Science

We are looking for a full-time research assistant to work under the direction of Dr Arun Advani and Dr Andy Summers. You will join a friendly and dynamic research team consisting of 3-5 research assistants, plus other collaborators, working on cutting-edge research into the UK tax system. Our research has a strong policy dimension and is regularly reported in UK and international media. We place particular emphasis on career development, supported by exposure to a range of research tasks and mentoring from the lead researchers. 

Your research will focus on quantitative analysis of the characteristics, behaviours and impacts of the UK’s ‘super-rich’ (individuals with very high incomes and/or wealth), using administrative tax data accessed via the UK tax authority’s secure research facility, HMRC Datalab. Recent projects include analysis of the UK’s ‘non-dom’ regime, top-end migration, capital gains, and evaluation of polices for taxing wealth in the UK. Further details are available from the lead researchers’ websites. You will also contribute to new research investigating the wider economic impacts of the super-rich on the UK economy. 

The successful applicant will perform a variety of tasks providing excellent preparation for doctoral programmes in public economics or a career in quantitative analysis of public policy. As well as data cleaning, validation and analysis, you will contribute to research designs, prepare and deliver presentations to academic and policy audiences, and edit academic papers. There will also be opportunities for co-authorship of papers and reports where this is merited by significant independent intellectual contribution. 

Candidates must have:

• Completed (by start date) Master’s degree in economics or other quantitative social science
• Ability to comprehend and apply complex technical information about the tax system
• Excellent quantitative data analysis skills including experience or training in analysis of large datasets
• Ability to conduct data cleaning and validation efficiently and with excellent attention to detail
• Excellent practical proficiency in the use of R
• Fluency in written and spoken English
• Ability to plan, prioritise and manage own workflow efficiently, including via communication with other team members
• High level of initiative and desire to make independent intellectual contribution to projects