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 (GBD); 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 are 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 outstanding opportunity for a Data Analyst on the GBD BIRDS team (Brain, Backpain and Other MSKs, Injuries, Renal, Respiratory, Diabetes, Drugs, and Sensory), focused on supporting injuries estimation.
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. The Surge Team supports research teams through temporary assignments to help meet deadlines, manage unexpected challenges or changes in scope, and fill in where staffing has fallen short. The BIRDS team takes on the challenging scientific endeavor of estimating the global burden of 33 injuries, including road injuries, interpersonal violence, drowning, and more, by leveraging large amounts of data, a complex analytical framework, and a global collaborator network.
The main purpose of the Data Analyst position is to provide support to key research projects through database management, data quality management, computational support to multidisciplinary research projects, data extraction and formatting, and providing key inputs for papers and presentations. Data Analysts must develop an understanding of different research needs and analytic functions across multiple projects to best meet research needs. Data Analysts 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.
This position calls for dexterity working with complex databases and the ability to assess, transform, and utilize quantitative data using multiple coding languages (R, Python, SQL, Stata). 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 team. This position is contingent on project funding availability.
DUTIES AND RESPONSIBILITIES
- 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 Python (required) and R (desired).
- 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 apply analytic skills to better understand complex information in a systematic way.
- Strong quantitative aptitude.
- Flexible attitude and interest in moving around to a variety of different research teams, getting a broader range of experience, rather than focusing on a particular research area or team.
- 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: https://www.healthdata.org/about/mission-vision/DEI.
- Demonstrated success in developing code in SQL, Stata, or other coding languages.
Condition of Employment
- 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.