Terms of employment: Contract
Project duration : Four years
Duration of contract: one year with possible extension
Place: Ethiopian Public Health Institute, Addis Ababa
Reporting to: National Data Management Center for health (NDMC)
Background
The National Data Management Center for health (NDMC) at the Ethiopian Public Health Institute (EPHI) is a responsible center to centrally archive health and health related data, process and manage health research, apply robust data analytic technics, synthesis evidence and to ensure evidence utilization for decision making by the Federal Ministry of Health (FMoH) and other relevant stakeholders at local, sub-national and national and international levels. NDMC has collaborative partnership with Institute for Health Metrics and Evaluation (IHME), University of Washington and has established a Burden of Disease (BoD) Unit. The BoD Unit is responsible for data mapping, collecting, reviewing and archiving available health and health related data in the country and for producing national and subnational burden of disease estimates collaboratively with Global Burden of Disease (GBD) Study centered at IHME for population and demography, mortality and risk factors for a range of communicable diseases, non-communicable diseases, maternal newborn and child health, nutrition and for injuries. The unit creates platforms for translating BoD evidence for decision and policy at national and subnational levels. The NDMC is looking for high caliber staff for this collaborative project
Roles 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.
· Responsible for the design of logical disease models based upon analysis of complex heterogeneous health research data archived at EPHI National Data Management Center for health.
· Explore and adapt conceptual and logical health research data models to generate strong evidence, predict and forecast the occurrence or trends of diseases an epidemics.
· Create, refine and distribute conceptual and logical data analysis models that help to integrate, triangulate and generate strong output for action
· Works closely with CSA, EDHS, MoH, HDSS sites and other institutes working on generating health research, surveillance and routine data.
· Coordinates and leads all modeling activities done at EPHI.
· Strong decision making skills and the ability to work uninterrupted on a focused project
· Works under limited supervision and within deadlines but also know when to seek help, and to work as part of a fast paced and integrated team
· Maintain, update, and adapt databases containing health data from multiple sources such as surveys, vital registration systems, administrative records, and published studies relevant to NDMC research priorities
· 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.
· Develop and implement algorithms or procedure to assess data quality.
· Coding and re-coding data contained within various databases to identify patterns by compiling Excel spreadsheets and using Visual Basic for Applications
· Be capable of intensive research and possess robust problem-solving skills, along with a strong familiarity with data warehousing, data mining and data mapping
· Be capable of presenting their findings clearly and accessibly in the form of reports, publications and spoken communications with colleagues, national and international audiences.
· PhD degree in Biostatistics, Epidemiology, Mathematics (Applied) or data science
· Four years proven experiences on health and health related data and big heterogeneous data analysis
Desired skills and experiences
· Enough experience on methodological foundations, including for example, causal inference, data systems design, deep learning, experimental design, modeling of structured data, random matrix theory, non-parametric Bayesian methods, scalable inference, statistical computation, and visualization
· Experiences in integrating, analyzing and triangulating big heterogeneous health research data
· Experience in mathematical modeling and prediction
· Experience in computer programming such as R and Python
· Experience in Parallel programming and using of HPC clusters
· Demonstrated ability to gather, analyze, and synthesize data from various sources and produce graphics and tabular data presentations.
· Excellent written and verbal communication skills.
· Organized and self-motivated. Ability to manage multiple tasks and meet demands of a fast-paced environment with changing priorities.
· Dedicated team player with flexibility to work with and without supervision.
· Experience with SAS/STATA, SPSS, R, advanced excel
· Capable of independently managing time and the tasks associated with a fast paced research agenda and strong organizational objectives