Associate, Maternal and Newborn Health at the Clinton Health Access Initiative (CHAI)

Clinton Health Access Initiative - Founded in 2002, by President William J. Clinton and Ira Magaziner, the Clinton Health Access Initiative, Inc. (CHAI) is a global health organization committed to strengthening integrated health systems and expanding access to care and treatment in the developing world. CHAI’s solution-oriented approach focuses on improving market dynamics for medicines and diagnostics; lowering prices for treatment; accelerating access to lifesaving technologies; and helping governments build the capacity required for high-quality care and treatment programs.

We are recruiting to fill the position below:

Job Title: Associate, Maternal and Newborn Health

Location: Abuja

Overview

• We are seeking to hire an Associate, Data science and analytics for its MNH program to lead monitoring and evaluation for its new grant.
• This 3-year grant will strengthen community maternal and neonatal mortality data generation by leveraging existing structures and provide insights into the burden of unreported maternal and neonatal deaths.
• Direct beneficiaries of this project are underserved women and newborn children, especially in rural communities.
• The generation of comprehensive maternal and neonatal mortality data through this project will empower community leaders, LGA government officials, and state government officials with tailored information and knowledge to reduce maternal and neonatal mortalities at the lower levels. In addition, this investment will support PHC workers in identifying medical and social factors contributing to maternal and perinatal deaths, providing opportunities for specific interventions to improve maternal and neonatal health outcomes.
• Furthermore, the project will empower pregnant women who deliver at home to access post pregnancy family planning services including post-abortion care and FP, which are typically unavailable for them. It will also strengthen reporting and visibility of post-pregnancy family planning data to improve FP program planning.
• Overall, the FP services provided through this project will empower women to make informed decisions about their body and family size, further supporting the achievement of gender equality and reduction of maternal and neonatal mortality. These are key to achieving Sustainable Development Goals 3 and 5.
• The Associate will join the CHAI Nigeria Sexual, Reproductive, Maternal and Neonatal Health Program portfolio team and will lead program efforts to expand and improve the generation of community level maternal and neonatal mortality and post-pregnancy FP data. We are seeking highly motivated individuals with outstanding credentials, analytical ability, and communication skills.
• The successful candidate must be able to function independently and flexibly as well as build strong relationships with government officials and partners. Additionally, the successful candidates will adhere to the CHAI values of: resourcefulness, entrepreneurialism, flexibility, independence, humility, and work ethic.
• The Associate MNH will be based in Abuja, Nigeria, with up to 50% domestic travel in the first year and subsequently reduced travel over time.

Responsibilities

• Work with the national and state CHAI teams and respective state government stakeholders to conduct a review and update the CBHMIS including the design, data reporting processes and tools
• Build and implement state-of-the art scientific algorithms to support outcomes data reporting using CBHMIS data
• Apply creative solutions to deliver data-driven insights on CBHMIS data and develop visualization tools for routine review by policy makers and critical decision makers who need to use the data
• Participate in national M&E TWG meetings and interact closely with FMOH and other partners working on the generation of community based
• Oversee the development and implementation of training plans for traditional leaders and other identified community level agents for collection, collation, and reporting of maternal and neonatal mortality, and PPFP data at community level
• Help state teams to better understand the data analytical processes and outputs and optimize protocol designs including the development of IEC materials and job aids.
• Design state level models to aggregate and curate state generated CBHMIS data and develop a national level dashboard to inform real-time tracking of generated data.
• Share complex statistical results in meaningful ways with stakeholders at various levels – health workers, LGA and state officials, traditional and community leaders, National level stakeholders and internally at CHAI.
• Help to assess technologies for the deployment of an AI-based platform to use CBHMIS generated data for predictive modelling, contribute to the building of the AI platform, and play a major role in building the data analytics ecosystem
• Initiate and lead the development of scientific articles and papers from results generated in the program, secure ethical approval where necessary
• Continually explore and pilot new data science opportunities to address identified public health gaps, demonstrate potential value, and write concept notes and proposals to secure funding
• Provide technical leadership to the FMOH on the integration of CBHMIS data into DHIS and support the process for adoption and roll out
• Any other responsibilities as assigned by the Program Director or Country Director

Qualifications

• Bachelor’s Degree in relevant field (Science, Engineering, Technology or within Biotech); Master’s Degree in Public Health with Concentration in Biostatistics, Epidemiology or other advanced Master’s degree is preferred
• 2-3 years of relevant experience
• Solid understanding and working knowledge of data science and digital health
• Strong problem solving, analytical thinking and communications skills e.g., explaining technical topics to non-technical colleagues, translating government data requests into data science strategy, effectively presenting to key decision-makers
• Data-management skills, e.g., cleaning/organizing data, data preparation, data collection, data integration across different data sources, data storage, database management
• Some experience in the management of big data and multivariate statistical methods such as the usage of statistical modeling techniques, including linear, logistic regression, principal component analyses and Clustering
• Proficient with at least one of the programming languages: Python, R, C++, or, Java
• Experience with developing and deploying descriptive, predictive, and prescriptive models
• Experience with a variety of algorithms, including AI/ML and deep learning is required
• Ability to multi-task and to be effective in high-pressure situations
• Ability to work independently on complex projects
• Ability to travel
• Experience in international development or global health is a plus 

Application Closing Date
Not Specified.

Method of Application
Interested and qualified candidates should:
Click here to apply online