FHI 360 recrute un Spécialiste de la gestion des données sur l’alphabétisation, Kigali, Rwanda
Job Description
Literacy Data Use Specialist, USAID-Tunoze Gusoma (Schools and Systems) Project
FHI 360 is a global development organization, with a rigorous, evidence-based approach to human development. Our team of professionals includes experts in education, health, nutrition, economic development, civil society, environment, and research. FHI 360 operates from over 60 offices with more than 4000 employees in the United States and around the world. Our commitment to partnerships at all levels and our multidisciplinary approach allows us to have a lasting impact on the people, communities, and countries we serve by improving the lives of millions. We are currently seeking qualified candidates for the position of Literacy Data Use Specialist for the USAID Tunoze Gusoma Schools and Systems project in Rwanda.
Project Description
The USAID Tunoze Gusoma (Schools and Systems) activity is working to strengthen the education system to enable all pre-primary and lower primary school and classroom environments to be of high quality, inclusive, and focused on the learning of foundational reading skills.
Specifically, the five-year activity is working to improve learning outcomes by focusing on increasing Kinyarwanda literacy skills of boys and girls through primary 3 (P3) through four intermediate results: (IR1) Pre-primary education system enhanced to develop, promote and improve emergent literacy, (IR2) Lower primary reading classroom instruction improved, (IR3) School environments improved for increased lower primary reading outcomes, and (IR4) Education management systems strengthened for improved literacy outcomes.
Position Description
Embedded in Rwanda National Examinations and School Inspection Authority (NESA)’s department of examinations, and under the co-supervision of USAID Tunoze Gusoma’ s System Strengthening Advisor and NESA’s Head of Examinations Department, the Literacy Data Use Specialist will collaborate with the technical team at NESA, MINEDUC and other development partners to enhance the Comprehensive Assessment Management Information Systems (CAMIS system), specifically enabling it to effectively handle the update and utilization of literacy data. Additionally, the Specialist will design and implement continuous capacity-building programs for NESA staff in charge of CAMIS use and management.
Specifically, the Literacy Data Use Specialist will collaborate closely with NESA to enhance the project’s capacity in integrating the Local Early Grade Reading Assessment (LEGRA) data system into CAMIS. He/She will collaborate with NESA Software developers to enhance the CAMIS infrastructure (support the flow, storage, processing and analysis of data in the system), and enabling it to effectively handle all LEGRA data from schools. This will ensure the systematic utilization of this data, in conjunction with other sources, to make well-informed decisions at both national and local levels. These decisions will aim to improve reading instruction and literacy learning outcomes for all students, with a particular focus on implementing changes and providing targeted support at the district, sector, and school levels. On the other side, the Literacy Data Use Specialist will be responsible for organizing the capacity building activities of NESA staff and teachers to understand and use of LEGRA data into CAMIS.
Job Responsibilities:
CA-MIS System Improvement:
- Collaborate with a team of skilled software developers at NESA and MINEDUC to seamlessly integrate LEGRA into CAMIS.
- Ensure that the collected LEGRA data are accessible to all education stakeholders, empowering them to make informed decisions and effectively plan.
- Work closely with the technical team responsible for CAMIS infrastructure to enhance the system’s capabilities to accommodate LEGRA scores from every student.
Capacity Building:
- Design and implement continuous capacity-building programs for NESA staff in charge of CAMIS use and management.
- Provide technical assistance to NESA in enhancing the teachers ‘capacity to utilize data generated by CAMIS to facilitate students’ remedial measures.
- Collaborate with NESA to offer comprehensive assistance in managing the LEGRA data collection and data visualization systems at different levels. This entails handling various aspects such as back-end technology, data cleaning, data management, data analysis, visualization, and more.
Improve the quality of literacy data generated by the system:
- Assist NESA in developing modules and tutorial videos that encompass key concepts, particularly those pertaining to the collection and utilization of high-quality LEGRA data through CAMIS
- Provide support in delivering training sessions to teachers, system managers, and users, ensuring their comprehensive comprehension of these concepts: LEGRA data fields, metadata, and the proper archiving of LEGRA data records, etc.
- Collaborate with NESA to thoroughly examine/analyze the LEGRA data gathered via CAMIS, ensuring the data’s high quality.
Dashboard Development:
- Based on the specifications provided by the Tunoze Gusoma team, work in collaboration with NESA to develop customized dashboards for LEGRA reports in CAMIS for both central and decentralized levels
Operational Use:
- Ensure efficient utilization of CAMIS by different stakeholders within the education system, ranging from schools, sectors, districts, to the national level.
- Work closely with NESA to guarantee regular accessibility of literacy data to system users.
- Support NESA with the CAMIS databases by supporting literacy-related functions as prioritized in work planning by Tunoze Gusoma and NESA.
- Support NESA coordination on LEGRA data visualization and use, as well as supporting NESA as needed in responding to needs expressed by external entities for LEGRA data (Rwandan govt and NGOs and development partners).
- Support Tunoze Gusoma efforts to promote lower primary teachers’ use of evidence-based and inclusive literacy pedagogy, and remedial reading instruction as informed by LEGRA data collected through CAMIS.
Transparency and Accessibility of literacy data:
- Collaborate with NESA to enhance public awareness regarding CA-MIS and the valuable data it generates, with a particular focus on literacy data.
- Support CA-MIS users about the significance and implications of literacy data generated from CA-MIS, ensuring a clear understanding of its purpose and benefits.
- Work with NESA to identify needs, gaps or challenges for LEGRA implementation at national, district, sector and school levels, and to continually improve LEGRA planning and implementation processes, and using literacy data at each of these levels.
Minimum required Skills and Qualifications:
- Bachelor’s degree or master’s in database management, computer science, M&E, data science, research and evaluation or education assessment and evaluation.
- At least 5 years of experience managing systems of data collection analysis, visualization, and data-driven decision making.
- Experience, or at least a working familiarity with JavaScript, PHP, Python, Hands-On SQL, Web API, Node.js, etc.
- Ability to work with source code and version repositories.
- Proven capacity to work with Rwandan government counterparts.
- Strong understanding of the Rwandan education system preferred.
- Demonstrated experience/ proficiency in programming/ statistical analysis.
- Expertise in data management, data analysis, and ability to navigate across different databases (data structures and software)
- Expertise in data process modeling
- Experience with literacy data collection, management, and use (EGRA/LEGRA or other), preferred.
- Demonstrated leadership, versatility, and integrity.
- Excellent written and oral communication skills in English
This job posting summarizes the main duties of the job. It neither prescribes nor restricts the exact tasks that may be assigned to carry out these duties. This document should not be construed in any way to represent a contract of employment. Management reserves the right to review and revise this document at any time.
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