Current Opening
Market Intelligence Analyst
The Opportunity
AgentZero is an early-stage startup building AI-powered tools for the energy sector, transforming how the industry accesses and uses market intelligence. We move fast, we ship constantly, and there is always more to do than there are hours in the day. If you thrive under pressure and want to be challenged every single day, this role will suit you. If you are looking for a quiet life, it won’t.
We are looking for a Market Intelligence Analyst to join the founding team. Our goal is to automate all our data and research workflows using AI. Your role is not to do everything manually — it is to use, oversee and continuously improve the automated systems that do the heavy lifting. You will manage AI-driven research pipelines, curate the data that feeds them, quality-check their outputs, and support customers with research queries.
Some areas still require significant manual work, and you should expect to roll up your sleeves where automation has not yet been cracked, always with an eye on how to solve the problem.
In return, you will gain hands-on experience with operating and building AI systems, large-scale data operations, and energy market intelligence — skills that are becoming some of the most sought-after in the modern economy. You do not need to be a software developer, but you should be comfortable working with data, genuinely curious about AI, and ready to take ownership from day one.
Key Responsibilities
Market Research & Intelligence
- •Manage automated research pipelines that track developments in offshore wind, interconnectors, cables, vessels and other energy transition sectors.
- •Configure and oversee automated monitoring of industry news, regulatory changes, planning applications, contract awards and project milestones.
- •Review and refine AI-generated analysis to identify trends and issues that require embedding in our systems.
- •Identify gaps in data coverage and proactively fill them.
Spatial Data
- •Assemble and maintain geospatial datasets relating to energy assets.
- •Work with GIS tools and spatial data formats (GeoJSON, Shapefiles, KML).
AI Agent Operations
- •Operate, monitor and manage AI agents that perform data enrichment, entity resolution, classification and quality control tasks.
- •Review and validate AI agent outputs, identifying errors, hallucinations or inconsistencies and feed corrections back into the pipeline.
- •Configure and tune agent prompts and parameters to improve accuracy and coverage.
Quality Assurance
- •Design and maintain automated QC processes, stepping in to resolve edge cases and complex problems. Fix issues.
Customer Support
- •Act as a first point of contact for customer queries relating to data, research and product functionality.
- •Respond to customer questions with accurate, well-researched answers in a timely manner.
Essential Skills & Experience
- •High work ethic, sense of urgency, and resilience under pressure — comfortable with the pace of an early-stage company.
- •Versatile and adaptable — happy to turn your hand to whatever needs doing.
- •Proactive and resourceful — you spot problems, you solve them, you fix them.
- •Experience working with structured data — comfortable with spreadsheets, CSV files, databases etc. Attention to detail with a methodical approach.
- •Ability to research and compile information from diverse sources efficiently.
- •Comfortable using AI tools (e.g. ChatGPT, Claude, Copilot) and understanding their strengths and limitations.
- •Excellent written and verbal communication skills.
Desirable Skills
- •Knowledge of the energy sector, particularly offshore wind, interconnectors or related infrastructure.
- •Experience with Python or scripting for data processing tasks.
- •Familiarity with GIS/spatial data tools (e.g. QGIS) and spatial data formats.
- •Understanding of AI/LLM concepts — prompting, agent workflows, RAG.
- •Experience in a startup or small team environment.
How to Apply
Please send your CV and a one-page cover letter to:
jasmine.beaumont@agentzero.energyIn your cover letter (no more than 350 words), please address the following:
What is the most complex data problem you have solved, and how did you approach it?
Generic applications will not be considered.