https:\/\/uwhires.admin.washington.edu\/eng\/candidates\/default.cfm?szCategory=jobprofile&szOrderID=190348&szCandidateID=0&szSearchWords=&szReturnToSearch=1<\/a><\/p>\nAs a UW employee, you have a unique opportunity to change lives on our campuses, in our state and around the world. UW employees offer their boundless energy, creative problem solving skills and dedication to build stronger minds and a healthier world.<\/p>\n
UW faculty and staff also enjoy outstanding benefits, professional growth opportunities and unique resources in an environment noted for diversity, intellectual excitement, artistic pursuits and natural beauty.<\/p>\n
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; Geospatial Analysis; 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.<\/p>\n
IHME has an outstanding opportunity for a Data Extraction Analyst on the Environmental Risk Factors team with the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study. The GBD is 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, and is the largest and most comprehensive effort to date to measure epidemiological levels and trends worldwide. The Environmental Risk Factors team is responsible for estimating exposure and health loss due to air pollution, water and sanitation, temperature, lead, radon, and occupational risk factors.<\/p>\n
The main purpose of this position is to provide highly specialized oversight and guidance of routine but complex extraction processes for input data used in modeling, papers, and presentations at IHME. The Data Extraction Analyst will provide support to key research projects through data extraction and formatting, and providing inputs for papers and presentations.<\/p>\n
The Data Extraction Analyst is expected to become specialized in data pertaining to relevant content areas and will consult with staff as needed. To create the array of indicators required, this position provides guidance on the extraction of all available relevant quantitative data from surveys, censuses, literature, and administrative records into central databases. This position will collate, clean, and extract data from survey, literature, vital registration, and other sources that have been identified. By doing so, they will catalog a library of data that will add to the foundation of the Institute. Relevant data include those on mortality, causes of death, epidemiology, and a range of determinants and risk factors, such as education, income, or air pollution.<\/p>\n
The position must have a strong command of a variety of research needs and analytic functions. The Data Extraction Analyst must be able to anticipate the needs of research teams, as well as other functional teams including the Global Impact Group, Technology Team, and Research Management as it pertains to the work of data extraction. This position will work with dynamic teams of researchers and staff at all levels and will work alongside other research staff on complementary projects requiring a foundational knowledge of IHME\u2019s work, as well as core technical skills and collective problem-solving. Overall, the Data Extraction Analyst will be a critical member of an agile, dynamic team. This position is contingent on funding availability.<\/p>\n
Responsibilities:<\/p>\n
Research command
\nBecome familiar with substantive areas of expertise to understand the dimensions and uses of health data and the analytic underpinnings of different research streams.
\nWork directly with researchers to trace back 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.<\/p>\n
Data management and quality assessment
\nPerform literature reviews and other forms of data seeking.
\nExtract, format, and transform data from multiple sources according to set protocols in consultation with researchers to best meet their needs. Sources include literature, surveys, censuses, administrative records, vital registration systems, and disease registries, among others.
\nDevelop and use protocols to identify problems with datasets and routine extraction processes, rectify issues, and systematize processes for future work.
\nImprove extraction process in order to save time or simplify the extraction process and\/or improve the quality of extractions.
\nMaintain, update, and interact with databases containing health data from multiple sources.
\nPerform quality assurance and routine diagnostics on data and databases.
\nAssess and contribute to decision-making about the definitions of fields for extraction and the organization and storage of input data.
\nArchive, catalog, and annotate datasets according to Institute standards to build a common library of materials for use by a wide set of researchers.
\nDocument extraction processes in order to ensure consistency in extraction across research teams.<\/p>\n
Publications, presentations, and data requests
\nCreate text, tables, figures, and charts for presentations and publications.
\nProvide referencing and other support for publications and presentations.
\nExecute queries on databases to respond to the needs of senior researchers and external requests from collaborators, media, policymakers, donors, and other stakeholders.<\/p>\n
General
\nCommunicate clearly and effectively while contributing as a member of the Institute.
\nWork closely with other team members to assist with relevant tasks, facilitate learning new skills, and help resolve emerging problems on different projects.
\nAttend relevant meetings, adhere to deadlines, and participate as a vital member to collectively advance team-level objectives.
\nServe as a resource to others in explaining approaches to data management and extraction.
\nParticipate in overall community of the Institute, carrying out duties as may be required of team members.<\/p>\n
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.<\/p>\n
REQUIREMENTS<\/p>\n
Bachelor\u2019s degree in sciences, global health, public health, or related field plus two years\u2019 related experience, or equivalent combination of education and experience.<\/p>\n
Additional Requirements:
\nMust have demonstrated competence with analytic tasks. Demonstrated familiarity and ability to assess, transform, and work with quantitative data from a range of sources.
\nStrong quantitative aptitude, desire to learn new skills, and ability to interpret complex analytic information.
\nStrong sense of focus and attention to detail.
\nAbility to learn new information quickly and understand complex information in a systematic way.
\nInterest in environmental health or population health research.
\nDemonstrated organizational skills, self-motivation, flexibility, and the ability to work and thrive in a fast-paced, energetic, highly creative, entrepreneurial environment.
\nStrong communication skills necessary.<\/p>\n
A commitment to working 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\u2019s DEI statement here: http:\/\/www.healthdata.org\/get-involved\/careers\/dei.<\/p>\n
Equivalent education\/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license\/certification\/registration.<\/p>\n
DESIRED<\/p>\n
Bachelor\u2019s degree in environmental or physical science.
\nBasic coding experience in R or Python.
\nProven interest in environmental risk factors: air pollution, water and sanitation, temperature, lead, radon, and occupational risks.<\/p>\n
CONDITIONS OF EMPLOYMENT<\/p>\n
Weekend and evening work sometimes required.
\nThis position is open to anyone authorized to work in the U.S. The UW is not able to sponsor visas for staff positions.
\nOffice is located in Seattle, Washington. This position is eligible to work fully remote in the U.S.; work schedule required to overlap 50% of IHME office hours, between 8 a.m. and 6 p.m. Pacific Time.<\/p>\n
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.<\/p>\n
Application Process:
\nThe 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 \u201cApply to this position\u201d. 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 \u201cMy Jobs\u201d 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.<\/p>\n
Applicants considered for this position will be required to disclose if they are the subject of any substantiated findings or current investigations related to sexual misconduct at their current employment and past employment. Disclosure is required under Washington state law.<\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":8699,"featured_media":34097,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_s2mail":"yes"},"categories":[14,15],"tags":[4,32,33,19,7,8,9],"_links":{"self":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/40749"}],"collection":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/users\/8699"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/comments?post=40749"}],"version-history":[{"count":1,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/40749\/revisions"}],"predecessor-version":[{"id":40795,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/40749\/revisions\/40795"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/media\/34097"}],"wp:attachment":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/media?parent=40749"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/categories?post=40749"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/tags?post=40749"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}