Data Analyst, Domestic Health Spending 🔥
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; Costs and Cost Effectiveness; 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 exciting opportunity for a Data Analyst to join the Resource Tracking Alzheimer’s and Dementia research team.
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 are tasked with developing an understanding of different research needs and analytic functions across multiple projects to best meet research needs. We are looking for an individual who is 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. Data Analysts are expected to interact successfully with a wide range of internal and some external partners, and to describe complex concepts and materials concisely. The role calls for dexterity in working with complex databases and the ability to assess, transform, and quality-control results, and to utilize quantitative data using R or Python coding languages 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.
The Resource Tracking Alzheimer’s and Dementia research team develops research intended to estimate health care spending for specific health conditions disaggregated by source for 195 countries and territories. Research from this team has been published in a wide set of journals, presented around the globe, and offered online through an interactive visualization. The research produced by this team will extend existing global spending estimates on Alzheimer’s disease and other dementias and Parkinson’s disease; conduct a deeper dive into both formal and informal costs of dementia in the US; and conduct data collection on global spending on these diseases. The team’s Data Analyst will work closely with the faculty lead, researchers, and a team of data analysts and data services specialists. This position will be responsible for a number of smaller, innovative projects focused on methodological developments to improve the spending estimation of both Alzheimer’s disease and other dementias and Parkinson’s disease. This position is contingent on project funding, which currently exists for two years.
- Become familiar with key research areas to understand the dimensions and uses of data and the analytic underpinnings of the Alzheimer’s and dementia spending project.
- 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.
- 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 datasets for use in ongoing analyses. Catalog 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 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.
- Participate in overall community of the Institute, carrying out duties as required as team members with other Institute members
- Bachelor’s degree in public health, epidemiology, statistics, biostatistics, math, economics, quantitative social sciences, or related discipline plus two years’ related experience, or equivalent combination of education and experience. As a rule, a bachelor’s degree is equivalent to 4 years’ experience.
- Demonstrated success in implementing complex analytic code in R or Python.
- Demonstrated ability in using databases with large-scale, complex datasets.
- Adept diplomacy and exemplary interpersonal skills required. Must be agile at forming respectful and rewarding relationships with people with different levels of experience and expertise from a variety of cultural, linguistic, and professional settings.
- Strong organizational skills and the ability to successfully manage multiple tasks and priorities to meet established and changing deadlines.
- Proven interest in health financing or health care spending, 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 collaborative environment.
- Ability to learn new information quickly and to apply analytic skills to better understand complex information in a systematic way.
- Strong quantitative aptitude.
- Weekend and evening work sometimes required.
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 Work 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.