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The Institute for Health Metrics and Evaluation (IHME) is an independent research center at the University of Washington. Its mission is to deliver to the world timely, relevant, and scientifically valid evidence to improve health policy and practice. IHME carries out its mission through a range of projects within different research areas including the Global Burden of Diseases, Injuries, and Risk Factors; Future Health Scenarios; Cost Effectiveness and Efficiency; Resource Tracking; and Impact Evaluations. Our vision is to provide policymakers, donors, and researchers with the highest-quality quantitative evidence base so all people live long lives in full health.

IHME is committed to providing the evidence base necessary to help solve the world’s most important health problems. This requires creativity and innovation, which is cultivated by an inclusive, diverse, and equitable environment that respects and appreciates differences, embraces collaboration, and invites the voices of all IHME team members.

IHME has an exciting opportunity for a Data Specialist on the Global Burden of Disease (GBD) Cancer team. A systematic, scientific effort to quantify the comparative magnitude of health loss due to diseases, injuries, and risk factors by age, sex, and geography over time, the GBD is the largest and most comprehensive effort to date to measure epidemiological levels and trends worldwide. The GBD Cancer team focuses on producing annual estimates, by country, of mortality and morbidity due to various adult and pediatric cancers. This position will work with a dynamic team of researchers and staff at all levels on an assigned research team. The Data Specialist is expected to become specialized in data pertaining to the content area and will consult with researchers as needed to amass relevant data for analysis, presentation, and publication. The Data Specialist will make use of innovative, cutting-edge analytic methods to help produce comparable estimates of the impact of diseases, injuries, and risk factors across the globe.

We are looking for someone who has a command of a variety of research needs and analytic functions. The Data Specialist must be able to independently translate requests into actionable results by writing and implementing novel code. The individual must be adept at navigating complex databases and analytic engines, and be able to design and interpret diagnostics and troubleshoot problems in order to resolve them. They must be able to independently interpret results to assess their quality and must be able to assess, transform, and utilize a broad array of quantitative data using Python or R. Frequently the individual will be given assignments where a desired end result is identified but there is no preset path laid for achieving it. The individual therefore must carry out individual planning and problem solving to resolve computational questions and produce results.

This position will additionally work alongside other research staff on complementary projects and will require knowledge and skill sharing and collective problem solving. Overall, the Data Specialist will be a critical member of an agile, dynamic research team. This position is contingent on project funding availability.


Research command
  • Exhibit command of one or more of the research areas at IHME, including their basic tenets, principles, and the nature of the data and results.
  • Develop mechanisms to reduce manual efforts of vetting and running our standard pipelines, as well as “future-proof” our methods – by producing more efficient code; creating streamlined comparative tools; and fixing errors sustainably – to most efficiently and transparently produce comprehensive estimates of mortality and morbidity due to cancer globally.
  • Work directly with researchers to identify the source of data used in models and results, understand the context of the data, and ensure that they are relevant to the analyses themselves.
  • Design and articulate ways to improve routine computational processes, including the relevant trade-offs of different approaches, for decision-making purposes.
  • Create and document efficient, effective, and replicable methods for processing data, developing code, organizing data sources, managing data quality, and explaining complex analytic processes.

Data management and analytics
  • Problem-solve computational and analytic challenges by investigating the data, understanding the root questions, and coming up with alternative measurement strategies.
  • Design, implement, and execute improvements to complex machinery to compute estimates of indicators. Optimize performance of machinery while running it to generate indicators as part of the annual production cycle.
  • Maintain, update, and improve upon databases and diagnostics of the data.
  • Enhance and execute analytic engines, statistical models, and tools to carry out functions responsive to the analytic questions to be resolved.
  • Execute queries and complete novel analytics to answer questions from senior researchers, collaborators, donors, and other stakeholders.
  • Create and execute diagnostics and summary reports on data, databases, and routine computational processes to assess performance and results.
  • Develop and use protocols to identify problems with datasets and routine computational processes, rectify issues, and systematize data for future analyses.
  • Assess and contribute to decision-making about what type of coding language and approach to use in accomplishing routine computational tasks.
  • Transform and format datasets for use in ongoing analyses. Catalog and incorporate these datasets into databases. Perform quality checks.
  • Develop novel representations of data and results for senior researchers and other stakeholders.
  • Assess results and provide input on validity.
  • Create new code functions to add to a common code library to make more efficient commonly needed tasks.

  • Create tables and figures, and generate text for presentations and publications, drawing upon data and information from a multitude of sources.
  • Communicate clearly and effectively while contributing as a member of the Institute.
  • Work closely with other team members to assist with relevant tasks, facilitate learning new skills, and help resolve emerging problems on different projects.
  • Serve as a resource to others in explaining analytic approaches, describing data, and instructing how to implement code. Participate in and/or lead internal trainings.
  • Participate in overall community of the Institute, carrying out duties as required as team members with other Institute members.

As a UW employee, you will enjoy generous benefits and work/life programs. For a complete description of our benefits for this position, please visit our website, click here.

  • Bachelor’s degree in social sciences, engineering, computer science, or related field plus four years’ related experience, or equivalent combination of education and experience.

Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.

Additional Requirements:
  • Demonstrated success in developing code in R or Python.
  • Interest in global health, population health, and/or ways in which quantitative research and data science can be used to create valuable global public goods.
  • Demonstrated self-motivation and evidence of self-direction. Agility with detailed information and data. Demonstrated flexibility and mature communication skills with an ability to thrive in a fast-paced, energetic, highly creative, and entrepreneurial environment.
  • Ability to learn new information quickly and apply analytic skills to better understand complex information in a systematic way.
  • Strong quantitative aptitude and agility making sense of new data.
  • Direct experience with quantitative data from a wide range of disparate sources, including surveys, registries, administrative data, vital registration systems, and research studies.
  • Demonstrated experience with one or more of the key research areas undertaken at IHME. Ability to explain the major tenets, principles, and purpose of a subset of the analytic work.
  • Experience interpreting results and diagnostics in order to help manage quality control system of the input data and results.
  • Ability to compartmentalize, illustrate, and explain how code implements analytic strategies.

A commitment to working to alongside others at IHME to illuminate the health impacts of systemic racism and to work within IHME to make our organization more diverse and inclusive. See IHME’s DEI statement here:

  • Demonstrated success in developing code in both R and Python.
  • Demonstrated success in developing code in SQL and/or Stata.

  • Weekend and evening work sometimes required.
  • This position is open to anyone authorized to work in the US. The UW is not able to sponsor visas for staff positions.
  • Office is located in Seattle, Washington. This position is eligible to work fully remote in the US; work schedule required to overlap 50% of IHME office hours, between 8 a.m. and 6 p.m. Pacific Time.
  • Committed to attracting and retaining a diverse staff, the University of Washington will honor your experiences, perspectives and unique identity. Together, our community strives to create and maintain working and learning environments that are inclusive, equitable and welcoming.

Application Process:
The application process for UW positions may include completion of a variety of online assessments to obtain additional information that will be used in the evaluation process. These assessments may include Workforce Authorization, Cover Letter and/or others. Any assessments that you need to complete will appear on your screen as soon as you select “Apply to this position”. Once you begin an assessment, it must be completed at that time; if you do not complete the assessment you will be prompted to do so the next time you access your “My Jobs” page. If you select to take it later, it will appear on your "My Jobs" page to take when you are ready. Please note that your application will not be reviewed, and you will not be considered for this position until all required assessments have been completed.