Earth Observation Analyst

Dublin
2 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineering Intern- AI Agents - 2025 Programme

DevOps Engineer

Data Scientist, AWS Industries

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

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.