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Data Analyst, Maternal and Child Health

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; 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 our Health Systems and Population, Fertility, and Mortality (PFM) Teams with a primary focus on the availability, use, and quality of maternal and child health care. This project focuses on assessing the services provided at antenatal healthcare visits, the location of births by level of facility (e.g. hospital, health clinic or other type of facility), and the supply and quality of maternal health care in health facilities. The Data Analyst will be involved in extracting and analyzing neonatal and infant deaths according to whether delivery occurred in a health facility or at home and assisting project staff with producing forecasts of select maternal care indicators into 2050.

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.


Research Command

  • Become familiar with key pregnancy care indicators (e.g. skilled birth attendance, in-facility delivery, Caesarian section, postnatal care, and antenatal care quality, including blood draw, blood pressure, tetanus vaccination, and urine analysis).
  • Become familiar with all-cause neonatal mortality (age 28 days and younger) and infant mortality (age 1 year and younger) for those delivering in health facilities versus those delivering at home.
  • Work directly with Health Systems and Population, Fertility, and Mortality (PFM) team members to collate, process and analyze vital registration data, sibling surveys, and other demographics data to characterize the availability and quality of services for pregnancy, delivery and postpartum at a subnational level, with a focus on: Burkina Faso, Ethiopia, India, Kenya, Nigeria, and Pakistan
  • Create and document efficient, effective, and replicable methods for extracting neonatal and infant mortality data by health facility, 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 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 social sciences, engineering, computer science, or related field plus two years’ related experience, or equivalent combination of education and experience.

Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.


  • Demonstrated success in developing code in R.
  • 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.
  • Deep 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 collaborative environment.
  • Ability to learn new information quickly and apply analytic skills to better understand complex information in a systematic way.
  • Strong quantitative aptitude.
  • 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’s DEI statement here.


  • Demonstrated success in developing code in Python, SQL, Stata, or other coding languages.


  • 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.
  • This position is funded for one year, with a possibility of extension contingent on the availability of funding.