Public Health Analytics | Data Science | Power BI & Python

Experience: 5+ years of relevant experience Domain: Public Health, Health Informatics & Programme Analytics

About the Role

We are seeking a technically strong Senior Data Analyst with a data science and engineering mindset to support public health programmes. The role focuses on understanding programme needs, developing analytical frameworks, managing complex datasets, and delivering interactive Power BI dashboards, advanced analyses and automated reports.

Using

Python, SQL and robust ETL workflows, the analyst will turn programme data into reliable evidence that supports performance monitoring, timely interventions and stakeholder decisions.

Key Responsibilities

· Programme needs & analytical frameworks: Engage with programme, M&E; and technical teams to understand objectives, operational workflows, indicators and reporting needs; translate these into KPIs, analytical frameworks, dashboard specifications and reporting plans.

· Power BI dashboards & data modelling: Lead end-to-end design, development, validation and maintenance of interactive Power BI dashboards; build efficient data models, DAX measures, drill-down views and decision-oriented visualizations.

· Advanced data analytics & interpretation: Apply descriptive, diagnostic and inferential analysis to identify trends, associations, geographic variations, performance gaps and potential drivers of outcomes; communicate defensible insights and practical recommendations.

· Python-based analytics & automation: Use Python (including pandas and relevant statistical libraries) for data manipulation, cleaning, transformation, exploratory analysis,



reproducible workflows and automation of recurring analytical tasks.

· Data engineering, SQL & ETL: Understand and integrate multiple programme datasets and information systems; design and maintain SQL queries, ETL workflows, analytical datasets and reliable data-refresh processes.

· Data quality & validation: Establish checks for completeness, accuracy, consistency, duplicates and anomalies; investigate discrepancies, document limitations and work with programme teams to close data-quality gaps.

· Reporting & stakeholder communication: Produce analytical and management reports, presentations and concise insight briefs; automate scheduled dashboard refreshes and report distribution to keep stakeholders informed.

· Programme performance improvement: Review programme coverage, service delivery, outcomes and operational bottlenecks; flag emerging issues and collaborate with implementation teams to monitor corrective actions.

· Public health & epidemiological analytics: Apply epidemiological and biostatistical methods to disease and service-delivery data; undertake disease profiling, forecasting or GIS/spatial analysis when relevant to programme needs.

· Technical leadership & continuous improvement: Guide junior analysts, document methods and data definitions, standardize quality assurance and identify opportunities to strengthen analytics,



reporting and data systems.

Required Qualifications & Technical Skills

1. At least 5 years of hands-on experience in data analytics, business intelligence, data science or data engineering; public health or healthcare programme experience strongly valued.
2. Strong proficiency in Power BI, including Power Query, data modelling, DAX, dashboard design, publishing and scheduled refresh.
3. Advanced Python skills for data manipulation, statistical analysis, automation and working with large or complex datasets.
4. Proficiency in SQL, relational databases, ETL, multi-source data integration and data-quality validation.
5. Strong analytical reasoning and ability to interpret results, assess data limitations and prepare transparent analytical reports.
6. Understanding of public health indicators, epidemiology, programme monitoring and evaluation, and stakeholder reporting.
7. Excellent communication, problem-solving, documentation and ability to independently manage analytical deliverables.

Preferred Qualifications · Bachelor’s or master’s degree in Data Science, Statistics, Computer Science, Epidemiology, Public Health or a related quantitative discipline.

· Experience with health information systems and public health data sources (e.g., Epicollect, DHIS2, ODK or KoboToolbox).

· Exposure to predictive modelling, machine learning, GIS/spatial analytics, cloud data platforms or advanced statistical methods.

Experience mentoring analysts and collaborating with multidisciplinary programme and technical teams

Pay: ₹700,000.00 - ₹900,000.00 per year

Benefits

- Provident Fund

Work Location: In person

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