Central Square Foundation
Website:
centralsquarefoundation.org
Job details:
Job Title: Project Lead (Data, Technology and Monitoring)
Type: Full Time
Team: Foundational Learning
Location: Patna, Bihar
About Central Square Foundation
Founded in 2012, Central Square Foundation is a non-profit philanthropic foundation working with the vision of ensuring quality school education for all children in India. CSF has a mission focused on ensuring high-quality foundational learning for all children in India. To achieve this, CSF works closely with state governments to improve foundational learning outcomes for children. To know more about us and our work, visit www.centralsquarefoundation.org.
About The Foundational Learning Team
The Foundational Learning (FL) team at Central Square Foundation supports States in designing and implementing state missions to ensure FLN learning outcomes for all children. Spread across states, the Project Management Units (PMUs) work closely with state bodies to co‑create mission goals, identify critical workstreams, set indicators of success, and regularly review mission progress.
Role Summary
The role will lead the design, roll‑out and scale‑up of data, technology and monitoring systems for the Bihar NIPUN Mission. The Project Lead will work closely with the State MIS/IT teams and the technology vendor to ensure strong governance, high‑quality product design, reliable implementation at scale and effective data use for decision making at state, district and block levels. The role is central to strengthening the feedback loop between data, classroom practice and student learning, and will report to the State Project Lead – Bihar while collaborating closely with the Bihar FL PMU members.
Key Responsibilities
Monitoring systems, application and governance
- Lead the design, development, roll‑out and scale‑up of the FLN monitoring application and overall monitoring architecture, in partnership with the State MIS unit and technology/vendor partners.
- Establish clear governance structures, roles and processes for requirements gathering, product road‑mapping, testing, release management, training and issue resolution.
- Conceptualise and institutionalise monitoring and data frameworks (indicators, tools, protocols, workflows) that enable state partners to track implementation fidelity and take timely corrective actions.
- Review and strengthen existing state MIS and monitoring approaches, identifying gaps and overlaps, and supporting integration, streamlining, change management and troubleshooting of large‑scale implementation issues (e.g., connectivity, devices, user adoption, data quality).
Dashboards, analytics, and program insights
- Design and operationalise user‑centric dashboards (state, district, block, cluster) using tools such as Excel, Power BI and other BI platforms to enable real‑time, data‑informed governance.
- Manage and analyse large‑scale administrative and assessment datasets from schools; derive actionable insights and translate them into clear recommendations for state leadership.
- Coordinate data flows across teams (assessments, training, academics, field monitoring) to ensure high‑quality, consistent, and usable data for decision‑making.
- Support periodic program reviews with leadership by curating and presenting concise data stories, insight notes, and progress reports.
- Analyze large‑scale assessment and student learning datasets from schools; set realistic but ambitious learning level targets with the state, and regularly track progress against these targets for different geographies and sub‑groups.
Strengthening monitoring culture and capacity
- Drive adoption and active usage of the FLN monitoring and performance data and associated dashboards by engaging with state, district, and block stakeholders and promoting a data‑driven decision‑making culture.
- Design and support capacity‑building for officials and field staff on data collection protocols, dashboard use, interpretation of indicators, and planning based on evidence.
- Present regular reports and briefs based on monitoring data for internal learning as well as external advocacy for policy and system reforms.
Field engagement and stakeholder management
- Conduct field visits for tool testing, dipstick studies, classroom observations, training observations, and feedback collection from different user groups.
- Build and maintain strong working relationships with key government stakeholders at state, district, and block levels, including SCERT, State MIS, education department officials, DIETs, BEOs, BRCCs/CRCCs and other mission structures.
- Coordinate closely with CSF's central team in Delhi and other state PMUs to ensure consistent, high‑quality monitoring data and cross‑state learning.
Desired Qualifications, Skills, And Abilities
- Bachelor's degree in economics, statistics, data science, public/education policy, engineering or a related field. Master's degree preferred.
- 6–8 years of experience in large‑scale monitoring, MIS or data systems. State‑level or similar system‑level experience strongly preferred.
- Experience working with government systems in education, health, nutrition or related sectors, ideally at state level.
- Hands‑on expertise in Excel and at least one BI/visualisation tool (e.g. Power BI, Google Data Studio/Looker Studio).
- Comfort using AI tools for analysis, summarisation and visualisation, and interest in trying new technologies.
- Excellent written and oral communication skills, with ability to prepare clear presentations, dashboards and briefs for senior leaders.
- Experience in foundational learning / education is preferred, but not essential for candidates with strong transferable skills and systems experience
- Working proficiency in Hindi and English, and confidence in engaging with officials at state, district and block levels.
Additional Details
Start Date: As soon as possible
Compensation: Remuneration will be competitive with Indian philanthropy pay scales and commensurate with the candidate's experience and qualifications.
Apply: Interested candidates can apply by clicking on the link in the post.
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