Analyst- Surveillance Intelligence
Support surveillance initiatives to enhance urban health outcomes.
Overview
Support surveillance initiatives to enhance urban health outcomes.
You have:
- Bachelor's degree in geography, geoinformatics, environmental science, public health, statistics, or a related field; a postgraduate qualification in GIS or public health is an advantage.
- 2-4 years of hands-on experience in spatial data work or health data analytics, with a portfolio of maps, risk visualisations, or dashboards produced for real programme or government decisions.
- Proficiency in QGIS or ArcGIS for spatial analysis and map production, and working knowledge of at least one scripting environment — Python (GeoPandas, Folium) or R (sf, tmap) for data processing and automation.
- Strong MS Excel skills for data cleaning, structured analysis, and reporting tools; experience managing and integrating heterogeneous data sources (shapefiles, health records, field survey outputs, environmental datasets) into a unified spatial database.
- Demonstrated ability to translate spatial analysis into outputs that non-GIS audiences — ward officers, health officials, programme managers — can read and act on without methodological explanation.
- Willingness to spend approximately 40% of time on field across three Ahmedabad wards during the survey phase for ground-truthing and data quality assurance.
- Fluency in English and Gujarati or Hindi.
- Familiarity with government health data systems such as IHIP, HMIS, or IDSP and an understanding of how disease notification data flows through the surveillance architecture.
- Experience designing mobile data collection forms on SurveyCTO, ODK, or KoBoCollect.
- Familiarity with spatial statistical methods, kernel density estimation, hotspot analysis, spatial autocorrelation, applied in a public health or environmental risk context.
- Experience with web mapping or dashboard platforms such as ArcGIS Online, Power BI with spatial layers, or Mapbox.
- Familiarity with AMC administrative geography, ward structure, or Smart City SCADL data infrastructure.
- Working knowledge of AI productivity tools such as Claude, ChatGPT, or Microsoft Copilot for accelerating data synthesis, analytical write-ups, or report drafting.
Potential interview questions
| Can you describe a project where you used spatial analysis to influence a public health decision? | This assesses your practical application of spatial analysis in a relevant context. | Provide a specific example detailing your role in the project and its impact. |
| How do you ensure data quality when managing large datasets? | This evaluates your understanding of data accuracy and integrity processes. | Pro members can see the explanation. |
| Describe a time when your communication of complex data led to action by stakeholders. | Pro members can see the explanation. | Pro members can see the explanation. |
| What strategies do you employ for effective stakeholder management? | Pro members can see the explanation. | Pro members can see the explanation. |
| Can you provide an example of how you have conducted an effective needs assessment for a health project? | Pro members can see the explanation. | Pro members can see the explanation. |
| Describe your experience with mobile data collection tools and their advantages in health data projects. | Pro members can see the explanation. | Pro members can see the explanation. |
| How would you handle unexpected challenges during field data collection? | Pro members can see the explanation. | Pro members can see the explanation. |
| What spatial statistical methods have you applied in previous projects? | Pro members can see the explanation. | Pro members can see the explanation. |
Added 1 month ago
-
Updated 2 days ago
-
Source:
clintonhealthaccess.org
