Geospatial AI Analyst
Impact: Location intelligence and spatial insights through expert geospatial AI analysis
Apply machine learning and AI techniques to geospatial data including satellite imagery, GPS data, and geographic information systems to solve problems in urban planning, environmental monitoring, agriculture, defence, and logistics. Build geospatial AI models, create visualisations, and extract insights from location-based data.
What the day looks like
- People interaction
- Moderate
- Team vs solo
- 60% Team / 40% Solo
- Client facing
- Sometimes
- Impact visibility
- Moderate
- Travel
- 5 to 10% for field work and industry events
- Schedule flexibility
- Flexible
- Remote work
- Hybrid
- Typical work hours
- 40 to 55 hours/week
- Stress level
- Low
At a glance
- Median salary
- $155,000
- Entry-level
- $85,000 - $115,000
- Senior
- $260,000+
- Growth by 2033
- 20% (faster than average)
- Demand
- Growing
- Freelance potential
- Low
- Salary growth potential
- High - 65 to 80% growth from entry to senior
- Typical student debt
- Low
Skills you'll use
Hard skills
- 55
Soft skills
- 45
Technical complexity: Moderate
How to get there
- Minimum education
- Master's Degree
- Licensing
- No
- Years to mid-career
- 2 to 4 years
- Years to senior
- 5 to 8 years
- Career switching
- Moderate
Where this career leads
How people arrive here
Where you can go from here
Typical progression
- GIS Analyst > Geospatial Data Scientist > Geospatial AI Analyst > Senior Geospatial AI Analyst > Head of Geospatial Intelligence
Future outlook
- Automation probability
- 15% low risk as geospatial AI requires deep technical expertise
- AI disruption risk
- Low
- Demand trend
- Growing
How people feel about it
- Overall satisfaction
- 7/10
- Meaning
- 7/10
- Work-life balance
- 6.5/10
- Prestige
- 7/10
- Social perception
- High