Terms of employment: Contract
Duration of contract: One year with possibility of extension
Place of Work: Ethiopian Public Health Institute, Addis Ababa
Reporting to: National Data Management Center for health (NDMC), Lead
Quantity: One
Background
The Ethiopian Public Health Institute (EPHI) has received financial support from the World Bank for Africa CDC Regional Investment Financing project to strengthen regional infectious disease detection and response systems. EPHI is the technical wing for the FMoH re-established as an exciting and dynamic autonomous federal government institute having its own legal entity in charge of three main objectives as expressed in the regulation number 301/2013: 1) Research on priority public health and nutrition issues (based on national public health research agendas), generate, translate and disseminate scientific and technological knowledge; 2) Surveillance for the early identification and detection of public health risks and prevent public health emergencies through adequate preparedness, alert, timely information to respond effectively and timely and ensure rapid recovery of the affected population from the impact of public health emergency; 3) national laboratory services on emerging and re-emerging public health emergency threats including referral diagnostic, back up services and analytical tests and support the capacity building of health and food science laboratories at the national level for quality laboratory services. In 2018, the institute has established a National Data Management Center for health (NDMC) to transform its data systems, evidence generation and data use for public health emergency responses.
NDMC is responsible to centrally archive health and health related data; ensure data governance and security; create platforms for data sharing, access and use; process and manage data by applying robust data analytic technics, integration of datasets and apply different analytical tools to generate and synthesis evidence; and ensure evidence utilization for decision making by the Federal Ministry of Health (FMoH) and other relevant stakeholders at local, sub-national and national continental and international levels; ensure relevant capacities are built at local, national and regional levels and to serve as canter of excellence.
The NDMC has the responsibility of implementing Africa CDC Regional Investment Financing Project (ACDCP) functions related to developing innovative interconnected and interoperable disease surveillance and reporting systems, networking regional and continental partners and with Africa CDC and to build data analytic, disease surveillance and reporting, undertaking integrated data analysis, evidence translation, and database development and evidence synthesis, digital platforms and data sharing and, will also serve as a regional and continental information hub. EPHI is therefore looking for a high caliber Data Science Expert with strong qualification and experience to contribute for the effective implementation of its aforementioned responsibilities.
ROLES AND RESPONSIBILITIES
· Apply innovative methods like machine learning / AI, data mining, big data analytics, predictive analytics, etc. and explore the use of innovative data science techniques on complex and heterogeneous health data to improve the analysis of health and health related data
· Play an analytical role researching, designing, implementing, and deploying full-stack scalable data analytics methods and machine learning solutions to challenge various health related issues
· Works with large sets of health data and establishes accurate and scalable analytics systems across varied applications.
· Modeling complex discovering insights and identifying health related gaps with algorithmic, statistical, visualization, and mining techniques.
· Translates research requirements into quick prototypes and enable the development of big data capabilities, frameworks, and governance processes in the NDMC and the health sector at large enabling more effective execution of data and analytics campaigns and the achievement of overall health related targets.
· Develops ML based and state of the art data science techniques for various problems including projections or predictive analytics; classification; clustering; pattern analysis; selecting features, building and optimizing classifiers, cleansing, and verifying the integrity of health data; performing Ad-Hoc analysis and so forth.
· Prototype, develop, test & execute data analytics & data visualization tools – including exploring how NDMC can make greater use of large volumes of unstructured data
· Develop effective result communication and dissemination methods through implementation of unique and creative visualization techniques.
· Support the development and enhancement of NDMC data systems interoperability and systematic adoption by providing advice on data science techniques.
· Provide capacity development support to strengthening data science capacity of the center through intensive trainings of advanced data analysis procedures and techniques.
· Contribute to, and/or lead the delivery of high-profile analytical products, in consultation with the relevant operational teams
· Develop partnerships with relevant actors in the area of data science for development
· Maintain, update, and carry out routine but complex computational processes that are central to generating results for ongoing researches through data science applications.
·Develop and use protocols to identify problems with datasets and routine computational processes, rectify issues, and systematize data for future analyses.
· 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.
· Help to develop and deliver training modules for short-term trainings focusing on the applications of data science for enhanced utilization of health datasets.
· Develop automated Python based libraries and computational tools for health data pre-processing, performing EDA, and developing, executing, verifying ML based models.
· Prepare concept papers, background analyses, and briefings to build support for the use of data analytics and data science techniques at NDMC
·The candidates must have short-term or long-term both online or in-person trainings in machine learning and deep learning (certificate is required to prove)
· Background in Statistics, Mathematics
· PhD in Statistics, Computer science, Biostatistics, Epidemiology and other related fields, and 6 years of relevant experiences or
· MSc in Statistics, Computer science, Biostatistics, Epidemiology and other related fields, and 8 years of relevant experiences or
· BSc in Statistics, Mathematics and 10 years of relevant experiences
DESIRED SKILLS AND EXPERIENCES
·Experience in machine learning and deep learning model deployments
· Published at least 6 public health related articles in reputable and peer reviewed journal (at least three of them as a first author); attach the abstracts of each publication.
· Strong problem-solving skills with an emphasis on product development.
· Advanced programming skill using statistical computer languages (R, Python, SQL etc.)
· Experiences in integrating, analyzing and triangulating big heterogeneous health research data
· Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
· Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
· Excellent written and verbal communication skills for coordinating across teams.
· A drive to learn and master new technologies and techniques.
· Experiences in statistical and mathematical modeling and applications
· Experience in mathematical modeling and prediction
· Experience with data visualization tools, such as D3.js, react-viz, Matplotlib, Seaborn, and GGplot, etc
· Experience in parallel programming and using of HPC clusters
· Practical skill in quick prototyping tools such as Streamlit and Shinny apps
· Demonstrated ability to gather, analyze, and synthesize data from various sources and produce graphics and tabular data presentations
· Demonstrated ability of summarizing large datasets visually that make complex results understandable at a glance
· 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.
· Capable of independently managing time and the tasks associated with a fast paced research agenda and strong organizational objectives
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