Analyst - Analytics & Insights

Job Description

Overview :The Clinton Health Access Initiative, Inc. (CHAI) is a global health organization committed to saving lives and reducing the burden of disease in low-and middle-income countries, while strengthening the capabilities of governments and the private sector in those countries to create and sustain high-quality health systems that can succeed without our assistance. For more information, please visit: https://www.clintonhealthaccess.orgCHAI has been working in India since 2004 in partnership with, and under the guidance of, the Ministry of Health and Family Welfare (MoHFW) both at the central and state levels on an array of high priority initiatives aimed at improving health outcomes. Currently, CHAI works across projects to expand access to quality care and treatment for HIV/AIDS, Hepatitis-C, tuberculosis, cancer, health financing and immunization. Additionally, CHAI is supporting the government of Madhya Pradesh (MP) on large-scale programs to arrest childhood and maternal mortality due to malnutrition, anemia, diarrhea and pneumonia, and helping increase access to quality Family Planning services.Background:Vector Borne Diseases (VBDs) represent a substantial burden in many low and lower-middle-income countries, including India that accounts for a significant proportion of the global burden of Lymphatic Filariasis (LF) and Visceral Leishmaniasis (VL). VL is endemic in about 54 districts in Bihar, Jharkhand, UP and WB with an estimated 130-165 million population at risk whilst LF is more widespread with cases reported across ~20 states/Union Territories and an estimated 550-600 million people at risk. Under the aegis of the National Vector Borne Disease Control Program, significant progress has been made towards elimination by 2025 and this ambitious vision is backed by strong political and robust programmatic strategy. Mass Drug Administration (MDA) for addressing LF has been completed and transmission interruption accomplished in 94 of the 256 endemic districts; however, transmission continues in 137 districts despite ~5-6 rounds of MDA underscoring the challenge of the task ahead.CHAI is privileged to support NVBDCPs bold vision of accelerated elimination of VL and LF by 2025. To that end, CHAI plans to staff a Technical Support Unit (TSU), an embedded team to work under the guidance of NVBDCP to achieve its vision through: 1) Strengthened technical and managerial support to NVBDCP management.2) Enhanced disease intelligence and analytics for improved programmatic decision-making3) Adoption of dynamic innovations across disease portfolios, and, effective and sustained investments in the space of NTDs/VBDs4) Support NVBDCP program in steering partnerships and multi-sector responseThe programme is enriched with a variety of data points that include the various centralized Information Communication Technologies (ICT) that exist such as the Integrated Disease Surveillance Programme (IDSP), Kalaazar Management Information System (KAMIS), Lymphatic Filariasis Dashboard Software, WHO district health Information System, Health Management Information System, Malaria Information System to name few that are operational within the VBD ecosystem between Government and stakeholders. However, as is the case in such situations that data does not come together, and the systems do not necessarily corelate as required for informed decision making.CHAI is seeking a highly motivated individual with outstanding credentials and demonstrated analytical abilities for the role of Analyst, Analytics and Insights. The Analyst would require to assimilate a variety of data points that include the various centralized Information Communication Technologies (ICT) that exist such as the Integrated Disease Surveillance Programme (IDSP), Kalaazar Management Information System (KAMIS), Lymphatic Filariasis Dashboard Software, WHO district health Information System, Health Management Information System, Malaria Information System to name few that are operational within the VBD ecosystem between Government and stakeholders. He/she would require bringing all the data sets together and scientifically represent data that provides for informed decision making. He/she would also be responsible in assessing the data needs, gaps in data sets and well as respond to the capacity need of the national programme.Responsibilities :1) Develop and socialize dashboards, pre-defined and custom defined reports for NVBDCP, state and sub-state functionaries to utilize for routine programme planning, decision making, monitoring and management.2) Innovate new approaches for generating VBD insights including but not limited to predictive modelling, clustering techniques, and machine learning etc.3) Contribute to programme strategy by developing purposive insights, tools and planning aids that help TSU and NVBDCP conceptualize multi-year system strengthening plans for control and elimination.4) Create periodic and automated analytics for specific aspects of the VBD programme such as performance of health system components like HR availability and capacity, commodities availability down to last mile, service delivery effectiveness to inform national and state programme manager action and outputs related to coverage and equity of mass drug administration campaigns and morbidity management and treatment.5) Support the crafting of monitoring & evaluation frameworks, and implementation and reporting mechanisms and optimize the existing ones where necessary in alignment with programme strategy and VBD context to facilitate effective oversight and management at the national, state and sub-state levels.6) Work closely with the TSU and NVBDCP teams to improve the overall data ecosystem and performance of the programme7) Support capacity building of NVBDCP staff on relevant competencies for sustained ownership and delivery8) Liaise with CHAI in-country and global teams on similar analytics initiatives9) Undertake any other duties as requested by the supervisorSalary offered: 8-10LPA,

Keyskills :
health systemsservice deliveryprivate sectorglobal teamsmachine learningmanagement information systemfamily planningglobal healthdisease control