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 is hiring for multiple Data Analyst positions on a number of different teams. We review and interview applicants on a rolling cycle. All applications received by March 18 will be included in this round of reviews. Those received after March 18th will be reviewed in the next round. Interviews for this round will be scheduled on April 3rd, 4th, and 5th. Placement onto a team is determined by specific needs of the team and candidates' qualifications.
These positions position must develop an understanding of different research needs and analytic functions across multiple projects to best meet researcher needs. The Data Analyst must be able to independently translate requests into actionable results through interactions with research databases, formulation of displays of results, and development of complex code to be applied to a variety of quantitative data. The position calls for dexterity working with complex databases and the ability to assess, transform, and utilize quantitative data using multiple coding languages such (Stata, Python, R, SQL). The individual must then quality control results to ensure that other team members have exactly what they need to incorporate the data and results into their own components of the analytic process, presentations, and papers.
Additionally, this position will work alongside other Data Analysts on complementary projects and will require knowledge and skill sharing and collective problem solving. Overall, the Data Analyst will be a critical member of an agile, dynamic research team. This position is contingent on project funding availability. Please note: These positions are open to U.S. Citizens and permanent residents; H1B visa sponsorship is not available.
Research Teams for which Data Analyst positions are currently available include:
Global Burden of Diseases, Injuries, and Risk Factors enterprise (GBD): A core research area for IHME is the Global Burden of Diseases, Injuries, and Risk Factors enterprise (GBD). 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’s aim is to provide policymakers, donors, and researchers with the highest-quality quantitative evidence base to make decisions that achieve better health.
Local Burden of Disease: IHME is seeking to revolutionize the way we track diseases around the world by developing innovative geospatial analytic methods to produce increasingly granular estimates of diseases and determinants. Just a few of the diseases this revolutionary work will touch on are pneumonia and its etiologies, diarrhea and its pathogens, malaria, HIV/AIDS, tuberculosis, Ebola, as well as select neglected tropical diseases. Through the development and use of geospatial techniques to synthesize information at the local level, and in partnership with key collaborators around the world, IHME will present results in interactive high-resolution maps to illuminate levels, trends, and disparities in health outcomes.
Central Computation: At the core of both the GBD and Geospatial Analysis is the need to take innovative analytic methods and devise ways to carry them out more easily and routinely. By creating and applying novel coding and computational solutions, the Data Analyst helps resolve thorny challenges to enable the timely and efficient production of high-caliber scientific and policy-relevant results. The solutions developed must allow databases, analytic engines, and creative data visualizations to function seamlessly with one another.
Resource Tracking: The Financial Resources for Health (FRH) research team is a longstanding core research team at IHME whose focus is to systematically, scientifically track resources spent on health and measure their impact. This research covers both domestic and international financing and uses a wide variety of data and statistical processes. To create health spending and impact estimates, this position collects, cleans, and manages a diverse set of quantitative data including household surveys, global databases, censuses, literature, and administrative records. Relevant data include a range of topics: health financing, epidemiology, demography, health systems, and health outcome determinants and risk factors such as education, income, and air pollution.
Forecasting and Cost Effectiveness: This research area is to help policymakers, donors, ministries of health and public health workers to effectively apply and scale up interventions by empowering them to review and compare the relative costs, efficacy, and impact of potential interventions and the modulation of different factors to the health system. By empowering these stakeholders with the best possible understanding of both what the future might look like based upon current assumptions and allowing them to compare different scenarios over time we equip them to better understand the tradeoffs inherent in different resource allocation decisions today and into the future.
Primary Data Collection: IHME aims to provide the best possible quantitative evidence base to policymakers, donors, and researchers in order to make decisions that lead to better health. Often that means providing as complete a picture as possible of health in a particular country, drawing upon a wide array of secondary data sources and helping prepare and execute primary data collection processes and systems. The Data Analyst will be integral to creating instruments for data collection, corresponding with field teams, and contributing to data management, data verification, and the creation of graphics and tables for analysis. This position will help with data quality management through an intensive period of data collection and will be instrumental in helping to present the key summary results derived from the data.
- Become familiar with substantive areas of expertise to understand the dimensions and uses of health data and the analytic underpinnings of different research streams.
- 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.
- Create and document efficient, effective, and replicable methods for extracting 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.
- Implement code solutions in order to answer analytic questions, perform diagnostics on results, and test and assess new methods.
- Maintain, update, and adapt databases containing health data from multiple sources such as surveys, vital registration systems, administrative records, and published studies relevant to demographic estimation
- Maintain, update, and carry out routine but complex computational processes and statistical modeling that are central to generating estimates of key indicators.
- Execute queries on databases and resolve intricate questions in order to respond to the needs of senior researchers and external requests from collaborators, media, policymakers, donors, and other stakeholders.
- Bring together data, analytic engines, and data visualizations in one seamless computational process.
- Use protocols to identify problems with datasets and routine computational processes, rectify issues, and systematize data for future analyses
- Transform and format data sets for use in ongoing analyses. Catalogue and incorporate these datasets into databases. Perform quality checks.
- Create tables, figures, and charts for presentations and publications.
- Provide referencing and other support for publications and presentations.
- Communicate clearly and effectively while contributing as a member of both the Institute.
- Work closely with other team members to assist with relevant tasks, facilitate learning new skills, and to help resolve emerging problems on different projects.
- Participate in overall community of the Institute, carrying out duties as required as team members with other Institute members
- Bachelor's Degree in social sciences, engineering, computer science or related field plus two years' related experience or equivalent combination of education and experience.
- Demonstrated success in developing code in R, Python, SQL, or other coding language.
- 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, ability to absorb detailed information, flexibility, and ability to thrive in a fast-paced, energetic, highly creative and entrepreneurial environment.
- Ability to learn new information quickly and to apply analytic skills to better understand complex information in a systematic way.
- Strong quantitative aptitude.
Condition of employment:
- Appointment to this position is contingent upon obtaining satisfactory results from a criminal background check.
- Weekend and evening work sometimes required.