The Institute for Health Metrics and Evaluation (IHME) is an independent research center at the University of Washington. Its mission is to monitor global health conditions and health systems, as well as to evaluate interventions, initiatives, and reforms. IHME carries out a range of projects within different research areas including: the Global Burden of Diseases, Injuries, and Risk Factors; Future Health Scenarios; Costs and Cost Effectiveness; Local Burden of Disease; Resource Tracking; and Impact Evaluations. The aim is to provide policymakers, donors, and researchers with the highest-quality quantitative evidence base to make decisions that achieve better health.
IHME has an excellent opportunity for a Research Scientist to join the Height-Weight team. We are looking for someone ready to advance in their career in global health research. As a Research Scientist you will be a lead on your research team by contributing to research design and training and mentoring junior staff. IHME researchers analyze and produce key estimates for their assigned research team and will assess all available relevant quantitative data – including those on causes of death, epidemiology, and a range of determinants such as education and income – from surveys, vital registration, censuses, literature, registries, and administrative records.
You will be integrally involved in producing, critiquing, improving, and disseminating results. You are someone that is capable of keeping your team on track to meet deadlines and research objectives. You already have a publication record, and at IHME, you will build out your portfolio with several peer-reviewed papers. You thrive in a collaborative work environment and are capable of working on multiple projects concurrently while meeting deadlines. You keep current of recent scientific, engineering and technical advances and are able to translate these into your research. This position is contingent on project funding availability.
- Exhibit command of risk factor estimation at IHME, including the methodology and its components.
- Independently carry out quantitative analyses and participate in reciprocal research projects. Interpret and vet results from junior staff, formulate conclusions and inform team leaders.
- Develop, quality check, and distribute complex data sets to be used in epidemiological and statistical analyses.
- Develop and implement new computational and statistical methods. Create, test, and use relevant computer code (R, Python, or equivalent). Maintain, modify, and execute analytic machinery that results.
- Draft presentations, manuscripts, and contribute to funding proposals. Lead and co-author scientific articles in peer-reviewed journals.
- Maintain scientific awareness and intellectual agility with data, methods, and analytic techniques.
- Oversee staff to include: hiring and training; leading workflow; priority setting; critiquing work and establishing quality standards; conducting regular performance assessments, providing mentorship and professional development for employees.
- Provide ideas and content for the development of internal trainings. Teach established trainings.
- Contribute to research design.
- Other duties as assigned that fall within reasonable scope of research team.
Master’s degree in public health, epidemiology, statistics, biostatistics, math, economics, quantitative social sciences or related discipline plus four years related experience or equivalent combination of education and experience.
- Growing peer network where sought out as having solid command with engineering/technical areas, a given disease, risk, key indicator, relevant methodological area, and the related data sources and scientific underpinnings.
- Excellent analytic, critical thinking, and quantitative skills.
- 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.
- Experience devising and executing statistical modeling techniques.
- Demonstrated ability to quickly recognize problems in results and identify root causes in data, methods, and code.
- Ease in designing, executing, and troubleshooting code in one or more languages (e.g. R, Python, Stata, SAS).
- Excellent written and oral communication skills required, including track record of success in co-authorship on multiple scientific papers, presenting results, and representing research at meetings.
- 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
- PhD or MD in public health, epidemiology, statistics, biostatistics, math, economics, quantitative social sciences plus two years’ experience preferred.
- Experience with machine learning, data mining, and analytic techniques.
- Experience mentoring and developing junior employees on soft and technical skills.
- Experience with project management methods.
- Peer-reviewed publication record.
Conditions of Employment: Weekend and evening work sometimes required.