IHME has an excellent opportunity for a Researcher to join the Costs and Cost-Effectiveness team. The team analyzes the cost-effectiveness of interventions and health spending by leveraging IHME’s experience, analytical framework, data bases, on cost-effectiveness, health financing, and burden of disease estimation and forecasts. To support universal health coverage, IHME will generate incremental cost-effectiveness ratios (ICERs) for a broad set of interventions at national and local levels by extending and improving our meta-regressing published estimates. ICERs are a metric for comparing health interventions, and represent the difference in cost between two possible interventions, divided by the difference in their effect. The meta-regression analysis will account for variation across epidemiological and sociodemographic context, study design and methods, and intervention characteristics as well as differences in disease burden, health care and delivery costs, health service efficiency.
The Researcher will be integrally involved in producing, critiquing, improving, and disseminating results. They already have a command of economics, epidemiology, statistics, disease modeling, or related interests and we will help you develop an understanding of our core research and methodology. Our researchers work with senior research leads and external collaborators and take part in the intellectual exchange about how to improve upon the results and disseminate the results.
- Develop a core understanding of cost-effectiveness analysis and meta-regressions methods.
- Under the guidance of experienced scientist and/or faculty, carry out quantitative analyses and statistical modeling to produce results designated on a given timeline as part of collaborative research projects.
- Extract data from various sources and databases. Format, transform, review and assess data sources to determine their relevance and utility for ongoing analysis. Understand key data sources and variations in these across and within countries.
- Develop and execute improvements to the analytic strategies and accompanying code that increase the relevance, quality, and use of results by external stakeholders while also improving code performance, diagnostics, and predictability or run-times.
- Review, assess, and improve results and methods.
- Consult with external collaborators and key stakeholders to resolve differences in competing sets of estimates, jointly understand and explain analytic approaches, and review and respond to recommendations for analytic modifications, new data, and ways of representing the results.
- Apply computational and statistical tools and algorithms for the preprocessing, analysis, and visualization of source data.
- Document code and analytic approaches systematically so that analyses can be replicated by other team members.
- Lead discussion in research meetings about results and analyses to vet, improve, and finalize results.
- Contribute to creation of presentations, manuscripts, and funding proposals. Co-author paper(s).
- Maintain scientific awareness and intellectual agility with data, methods, and analytic techniques.
- Other duties as assigned that fall within reasonable scope of research team.
REQUIREMENTS: Master’s degree in public health, epidemiology, statistics, biostatistics, math, data science, economics, quantitative social sciences or related discipline plus 1 year related experience or equivalent combination of education and experience.
- Demonstrated interest in health interventions and their effects upon population health.
- Demonstrated experience in population health methods or other applicable statistical analyses using large data sets, and ability to understand and explain their scientific underpinnings of those methods.
- Strong analytic, critical thinking, and quantitative skills
- Ability to professionally and effectively communicate and work with other staff at all levels in order to achieve team goals for the analyses and related outputs.
- Results and detail-oriented individual that can initiate and complete tasks under tight deadlines and changing priorities both independently and in a team environment. Flexibility with hours and workload is key.
- Proficiency with programming in R or Python and willingness to program predominately in Python.
- Excellent communication skills, both oral and written
- Ability to work both independently and in collaboration with a team
- A long-term interest in a Research Scientist position contributing to the overall mission of our research