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 outstanding opportunity for a Research Engineer to join Resource Tracking Team. The main purpose of this position is to design, implement, and support analytic engines and diagnostics related to tracking resources spent on health and measuring their impact.. This position must translate research objectives and complex operational requirements into efficient, easy-to-use, and optimized software that allows users to produce high-caliber scientific results. The position will ensure the routine operation of cause of death data standardization and correction analytic engines and diagnostic tools. They will problem-shoot and help data professionals and modelers to find solutions to challenges that arise in undertaking novel analyses. The position will also create new shared functions and tools to meet recurrent challenges and make the overall disease modeling, results review, and finalization process easier and more efficient.
This position requires a strong background in writing scientific software and an ability to translate researchers’ needs into a concrete software development plan. The individual will design and implement solutions that improve performance and can easily be utilized by other staff on the Resource Tracking team with variable coding experience. The position ensures the software developed is appropriately flexible, scalable, and efficient. This includes providing guidance and feedback to the Resource Tracking data professionals as they work on critical additions/modifications to the existing codebase to address analytical problems. The position calls for dexterity working with multiple coding languages (e.g. Python, R, SQL, Stata).
The individual must learn how multiple components of a complex analytical process relate to one another, learn the nature of the key indicators and variables being analyzed, and identify and implement ways to improve performance while maintaining high-quality and reproducible scientific results. Utilizing cutting-edge analytic techniques from a range of quantitative disciplines, IHME produces regular estimates of the key financial resources provided for health. This research illuminates the resources expended on health, including which organizations and bodies provide them, and which health areas are targeted. Resource Tracking generates annual estimates of global health financing; assesses macro unit costs; tracks resources provided for different diseases and risk factors; and widely measures expenditures that flow through the various functions of health systems in different countries. This work relies upon the collation of all available quantitative data from a variety of sources, including budgets, financial reports, tax filings, hospital records, healthy facility surveys, and claims data, among others. Through these efforts, major peer-reviewed publications, an annual policy report, and novel interactive tools are produced to help scientific and non-scientific audiences digest the results.
This position may additionally work alongside other teams on complementary projects and will require knowledge and skill sharing and collective problem-solving. Overall, the Research Engineer will be a critical member of an agile, dynamic research team. This position is contingent on project funding availability.
Research learning and methods development
- Exhibit command of the dimensions and uses of health data in the Global Burden of Disease (GBD) enterprise.
- Become familiar with the various inputs and process interdependencies that exist within the cause of death team’s computational structure.
- Develop, test, implement, and support analytic methods as appropriate.
- Explore new technologies and make recommendations as to their adoption.
- Design and articulate ways to improve routine computational processes, including the relevant tradeoffs of different approaches, for decision-making purposes.
Research software development
- Develop tools and diagnostics that are fully integrated into complex computational processes to enable non-expert users to routinely execute complex analytic processes and assess results
- Redesign and refactor existing code to improve efficiency and performance while maintaining high-quality and reproducible results.
- Design with flexibility in mind so that analytic tools can scale over time and modifications to methods can be easily incorporated
- Optimize code efficiency and parallelize across our massive (20,000+ CPU cores) computing cluster to enable researchers to quickly produce results.
- Follow software development best practices to document, test, and perform source control.
- Maintain, update, and carry out routine but complex computational processes that are central to generating cause of death estimates.
- Develop and use protocols to identify problems with datasets and routine computational processes, rectify issues, and systematize data for future analyses.
- Perform quality checks and audits of code from fellow staff.
Publications, presentations, and data requests
- Help create tables and figures, and generate text for presentations and publications, drawing upon data and information from a multitude of sources.
- Develop novel representations of data and results for senior researchers and other stakeholders.
- Communicate clearly and effectively while contributing as a productive member of both the Global Burden of Disease team and the Institute as a whole. Work closely with other team members to help them with relevant tasks, show them how to learn new skills, and help resolve emerging problems on different projects. Attend relevant meetings, adhere to deadlines, and participate as a vital member to collectively advance team-level objectives.
- Serve as a resource to others in explaining analytic approaches, describing data, and instructing how to implement code related to cause of death data.
- Participate in overall community of the Institute, carrying out duties as required as team members with other Institute members.
Bachelor’s degree in Biostatistics, Computer Science, or a related field and three years’ related experience in software development, or equivalent combination of education and experience.
- Demonstrated success in implementing code in Python, R, SQL, Stata.
- Must have demonstrated facility with analytic tasks and ability to participate productively in interdisciplinary research teams. Strong quantitative aptitude, desire to learn new skills, and ability to interpret complex analytic information.
- Strong sense of focus and attention to detail.
- Demonstrated familiarity with and ability to agilely assess, transform, and work with quantitative data from a range of sources.
- Ability to learn new information quickly and to apply analytic skills to better understand complex information in a systematic way.
- Interest in global health research.
- Demonstrated organizational skills, self-motivation, flexibility, and the ability to work and thrive in a fast-paced, energetic, highly creative, entrepreneurial environment.
- Strong communication skills necessary to discuss complex databases and computation items with lead faculty and data professionals.
- Master’s degree in Biostatistics, Computer Science, or a related field
Conditions of Employment: Evening and weekend work may be required.
Please Note: Priority consideration will be given to applications received on or before April 26.