The Happier Lives Institute (HLI) connects donors, researchers, and policymakers with the most cost-effective opportunities to increase global wellbeing. Using the latest subjective well-being data, we identify the problems that matter most to people and find evidence-based ways to solve them.
The Senior Researcher will lead and grow our team of quantitative researchers to identify the most cost-effective interventions for increasing subjective wellbeing. Our current priorities for further analysis are deworming treatments, poverty alleviation programmes, digital mental health interventions, and the regulation of air quality and lead. The team currently consists of two full-time research analysts but we plan to expand the team in the coming years. One of our team members has written about the life of an HLI researcher here.
Key roles and responsibilities
- Research (approx. 60%).
- Conduct literature reviews to identify the most cost-effective interventions and policies for increasing subjective wellbeing.
- Our current focus is on micro-interventions in low-income countries, but our scope is likely to expand in the future. Example: See our comparison of cash transfers and psychotherapy.
- Construct cost-effectiveness models using Monte Carlo simulations and other computational methods to account for uncertainty. Example: See our report on estimating moral weights.
- Create and refine methods to improve the quality of our cost-effectiveness analyses. Examples: Explicitly incorporate philosophical views, adjust effects due to bias, and convert between different types of wellbeing measures.
- Horizon scan for promising interventions by keeping up with the latest literature, attending relevant events, talking regularly with domain experts, and thinking critically about mechanisms for bringing about positive change. Example: See our report on pain.
- In some cases, there may be the opportunity to submit papers for publication in academic journals. Example: See our cash transfers meta-analysis in Nature Human Behaviour.
- Management and coaching (approx. 30%)
- Manage and coach our team of quantitative researchers.
- Set and achieve quarterly objectives for the team.
- Ensure that research projects are finished on time, on budget, and meet our high standards of quality and rigour.
- Help to develop our research agenda by identifying and prioritising potential research projects.
- Outreach (approx. 10%)
- Support the Communications Manager with promoting our research by writing blogs, appearing on podcasts, and speaking at events as required.
- Build a professional network of researchers, philanthropists, and policymakers who support our mission.
Experience and skills
- Dedication to conducting high quality, impactful research and working to improve global wellbeing.
- A degree in a quantitative subject such as economics, statistics, or mathematics (or another relevant social science subject).
- At least four years of relevant postgraduate research experience (which can include advanced degrees).
- Experience in supervising the work of other researchers.
- Excellent analytical skills and comfort working with quantitative methods and models.
- High proficiency in the evaluation and synthesis of empirical research.
- Strong statistical skills, which include proficiency with frequentist modelling techniques (general linear models and multilevel models), a good understanding of the assumptions underlying these models, and the ability to interpret these models correctly.
- Ability to work in R (or other coding languages such as MatLab, Python, Julia, or Stata).
- Excellent communication skills, particularly in writing, including the ability to clearly describe your reasoning, findings, and uncertainty.
- Desired skills and experience We don’t expect you to have all the skills and experience on this list. Plus, we want you to learn new skills in this role.
- If you are on the fence, please err on the side of applying.
- Comfort with meta-analytic methods such as extracting data from studies, standardising effect sizes, formally appraising the quality of evidence, and performing moderator analyses.
- Bayesian modelling, prior selection, and interpretation.
- Uncertainty propagation (Monte Carlo simulations) and sensitivity analysis.
- Understanding of psychometrics, such as validation and mathematical modelling of latent variables and Item Response Theory.
- Experience collaborating on research projects in GitHub or GitLab. R Markdown (or equivalent code-to-report technology).
- Strong data visualisation skills. Familiarity with the well-being science literature.