National Data Quality Assurance Officer

• Design the project’s data quality assurance framework within the first six weeks, including: a results chain from activities to outputs to outcomes, indicator definitions with precise measurement methodology, data sources, collection frequency, responsible persons, and reporting templates
• Develop and maintain the project’s central data tracker (Excel or database-based) covering all key indicators: community mobilisation numbers (sentinels identified, trained, active), training outputs (sessions conducted, participants trained by cadre and gender), IHIP reporting (signals reported, verified, time-to-verification, outcome classification), and system performance (verification rate, documentation quality, feedback loop completion)
• Receive data from State Data Quality Assurance Officers and District Coordinators on a fortnightly cycle. Cross-check submitted data against training attendance registers, IHIP system records (where accessible), and State Coordinator field visit observations. Flag discrepancies and resolve them before data enters the master tracker
• Produce monthly data summaries for the Project Lead: a two-page brief showing progress against each indicator, trends across districts, areas of concern, and recommended corrective actions. The brief should use simple charts and tables that make patterns visible at a glance
• Conduct data quality audits: visit each state at least once during the project (ideally around Month 5–6) to physically verify a sample of reported data. Select a random set of reported training sessions and check attendance registers, participant feedback forms, and follow-up records. Select a sample of reported IHIP signals and trace them through the verification chain. Document findings and share with the Project Lead
• Prepare the data sections of quarterly donor reports, ensuring that every number reported to the donor has a documented source and has been quality-checked
• Support the baseline data collection exercise (Months 1–2) by designing data collection tools, training Outreach Coordinators on their use, and supervising data entry and cleaning. The baseline establishes the starting point against which all subsequent progress is measured – getting it right is critical
• Design and support the mid-term and end-line competency assessment exercises. Develop assessment rubrics, train assessors, and analyse results
• Maintain a gender-disaggregated data system. Given that ASHAs and ANMs are almost entirely women, and MOs and DSO staff are predominantly men, gender disaggregation is not just a compliance requirement – it reveals whether training is reaching different cadres equitably and whether there are differential barriers to skill uptake. 

•     Post-graduate degree in statistics, epidemiology, public health, demography, or social sciences with quantitative research methods training
•     Minimum 4 years of experience in NCDC or State IDSP managing zoonotic diseases with at least 2 years managing programme-level data trackers
•     Strong skills in MS Excel (pivot tables, charting, data validation). Familiarity with Stata, R, or SPSS is desirable for baseline data analysis
•     Experience designing data collection tools for field use, including awareness of practical constraints (literacy levels of data collectors, connectivity issues, time limitations)
•     Experience with IDSP or any government health surveillance data system is a strong advantage
•     Fluency in English and Hindi. Ability to communicate data findings in plain language to non-technical audiences
•     Willingness to travel to project districts (estimated 4–6 trips during the project period) 

YRG is an equal-opportunity organisation. At YRG, we are committed to supporting inclusion and diversity as part of our values. We celebrate employee’s differences in abilities, sexual orientation, ethnicity, faith, and gender. Our team are people with different strengths, experiences, and backgrounds, who share a passion for improving people's lives. 

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