Remote Spatial Epidemiology information
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$63.4K is the 25th percentile. Wages below this are outliers.
$61K - $69K
16% of jobs
The median wage is $78.3K / yr.
$77K - $85K
13% of jobs
$96.5K is the 75th percentile. Wages above this are outliers.
$93K - $101K
9% of jobs
How much do remote spatial epidemiology jobs pay per year?
As of Aug 16, 2026, the average yearly pay for remote spatial epidemiology in the United States is $85,222.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $101,000.00 per year, depending on experience, location, and employer.
Remote spatial epidemiologists often work closely with professionals from public health, data science, environmental science, and GIS backgrounds. Collaboration typically involves regular virtual meetings, sharing and interpreting spatial data, and jointly developing study designs and reports. Effective communication and use of cloud-based tools are essential to coordinate tasks, discuss findings, and ensure data security. Building strong virtual relationships with team members helps streamline workflows and contributes to successful project outcomes.
Remote spatial epidemiology is a field that combines the study of disease patterns in populations (epidemiology) with spatial analysis, often using geographic information systems (GIS) and remote sensing data. Professionals in this field analyze how diseases spread and are distributed across different locations, often working remotely with digital tools and datasets. Their work helps public health organizations understand environmental and demographic factors that influence disease outbreaks. By working remotely, they can collaborate with global teams and access data from various regions without being physically present.
To thrive as a Remote Spatial Epidemiologist, you need a solid background in epidemiology, statistics, and geographic information systems (GIS), typically supported by an advanced degree in public health or a related field. Proficiency with spatial analysis tools like ArcGIS, QGIS, and statistical software such as R or Python is essential, along with familiarity with remote data collection techniques. Strong analytical thinking, attention to detail, and effective communication skills are crucial for interpreting complex spatial data and collaborating remotely with multidisciplinary teams. These skills and qualities enable precise analysis of disease patterns, inform public health interventions, and ensure effective remote collaboration on geographically dispersed projects.
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