National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Earth Observation Analyst

Dublin
4 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist (Loss Modelling)

Data Engineer-I

Sr. Data Scientist, FCGT...

Principal / Senior Data Scientist

Postdoctoral Fellow: Neurodegenerative Disease Spatial Transcriptomics and Machine Learning

Data Scientist II, Regulatory, Intelligence, Safety and Compliance (RISC)

Job Title: Earth Observation (EO) Data Scientist
Location: Ireland (Remote, with occasional client meetings and in-person training)
Must reside in Ireland

Salary: €55,000 - €60,000 per annum (depending on experience)
Job Type: Full-time
About the Role
Our client is seeking an experienced Earth Observation (EO) Data Scientist to join their team. This role is ideal for a professional with a strong background in EO data processing, machine learning applications, and cloud-based EO tools. The position is remote, but the candidate must be based in Ireland and available for occasional client meetings and training sessions.

Key Responsibilities

Process and analyze Earth Observation data, including optical and radar datasets.
Utilise common EO Python libraries such as GDAL, Pandas, and GeoPandas for data handling and analysis.
Develop and apply AI and machine learning models for EO applications.
Work with cloud-based EO platforms such as DIAS and Google Earth Engine (GEE).
Automate workflows and conduct time-series analysis for EO projects.
Develop and maintain scripts for Linux environments using Bash scripting.
Collaborate with clients and stakeholders to understand project requirements and deliver tailored solutions.
Document methodologies and findings clearly for both technical and non-technical audiences. Required Qualifications & Experience

Master’s degree in Earth Observation (EO), Geographic Information Systems (GIS), or a closely related field.
At least 4 years of industry experience working with EO data and processing techniques.
Strong knowledge of optical and radar data processing methods.
Experience in AI and machine learning model development and implementation.
Hands-on experience with cloud-based EO tools such as DIAS or Google Earth Engine (GEE).
Proficiency in Linux operating systems and basic Bash scripting.
Strong problem-solving skills and ability to work independently.
Excellent written and spoken English skills.
Must have permission to reside and work in Ireland (onshore applicants only). Benefits

Annual Leave: 22 days of holiday leave, increasing to 23 days with time served.
Additional Leave: Option to purchase extra annual leave.
Flexible Working: Work-from-home flexibility (full-time or part-time).
Family Benefits: Enhanced maternity and paternity benefits.
Pension Scheme: Employer-contributed pension plan.
Employee Assistance Programme (EAP):
Access to a health & wellness platform, including a digital gym, nutrition guides, and well-being tutorials.
EAP services for employees and their partners, including counselling support.
Health Insurance: Company-sponsored health insurance covering optical, dental, physiotherapy, and more.
Cycle to Work Scheme: Option to participate in the cycle-to-work programme.
Professional Development: Continuous professional development opportunities. Eligibility
Candidates must have valid permission to work and reside in the European Union and the Republic of Ireland. The candidate must currently reside on the island of Ireland for this position.
If you meet the criteria and are passionate about Earth Observation and geospatial analytics, we encourage you to apply

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.