Remote Sensing & EO Lead for Global Impact

Remote Sensing & EO Lead for Global Impact

Full-Time 35904 - 35904 £ / year (est.) No working from home possible
MAG (Mines Advisory Group)

At a Glance

  • Tasks: Lead innovative remote sensing projects to boost humanitarian efforts worldwide.
  • Company: MAG (Mines Advisory Group), a UK-based organisation making a global impact.
  • Benefits: Starting salary of £35,904, pension scheme, and generous leave policies.
  • Other info: Remote role with about 30% travel and opportunities for career growth.
  • Why this job: Make a real difference in humanitarian projects while travelling and innovating.
  • Qualifications: Proficiency in GIS software, machine learning, and a relevant degree required.

The predicted salary is between 35904 - 35904 £ per year.

MAG (Mines Advisory Group), based in the UK, seeks an expert in remote sensing for a remote role with about 30% travel. You will develop methodologies to enhance operational efficiency across humanitarian projects, focusing on innovation in data usage.

Candidates should have proficiency in GIS software and machine learning, alongside a relevant degree.

The role offers a starting salary of £35,904, increasing with service, and offers various benefits including leave policies and a pension scheme.

Remote Sensing & EO Lead for Global Impact employer: MAG (Mines Advisory Group)

MAG is an exceptional employer that prioritises innovation and impact in humanitarian efforts, offering a collaborative work culture where your expertise in remote sensing can truly make a difference. With a commitment to employee growth, you will have access to professional development opportunities and a supportive environment, all while enjoying competitive benefits and a flexible remote working arrangement that allows for meaningful contributions to global projects.

MAG (Mines Advisory Group)

Contact Details:

MAG (Mines Advisory Group) Recruitment Team

We think you need these skills to ace Remote Sensing & EO Lead for Global Impact

Remote Sensing
GIS Software Proficiency
Machine Learning
Methodology Development
Operational Efficiency
Data Usage Innovation
Humanitarian Project Experience