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Associate Data Analyst - Energy and Freight Markets

Vortexa

Vortexa

IT, Data Science
London, UK
Posted on Dec 7, 2024

About Us:

Vortexa was founded to solve the immense information gap that exists in the energy industry. By combining massive amounts of new satellite data, pioneering work in artificial intelligence and deep industry knowledge, Vortexa creates an unprecedented view of seaborne global energy flows in real-time, bringing transparency and efficiency to the energy markets and helping society as a whole.

Having secured over $60mil USD in funding, we are embarking on a period of rapid growth.

The Challenge:

Vortexa is looking for an Associate (Junior) Data Analyst to join our global Market Intelligence & Analytics Team, with an opportunity to have a direct impact on the ambitious growth plans of our company.

In this role, your responsibilities will include supporting global research and analysis tasks relating to energy trade flows, freight supply/demand fundamentals and oil inventories. You will conduct daily data validation and quality assurance operations including the manipulation, cleaning, testing and analysing of a variety of critical datasets. You will also learn how to use our internal tools and processes to help maintain data excellence on a day-to-day basis, leading to developing and refining such tools and processes.

You will work in close collaboration with experienced market and data analyst experts across our global team, collaborate on important data quality initiatives and present back your findings. You will also support the team in responding to ad-hoc client and internal escalation requests. Aside from close partnership with the analysis team, you will also work in very close collaboration with R&D (particularly data processing) and product teams.

You must be highly analytical, detail orientated and a driven self-starter with a positive, proactive approach to problem-solving in a fast-paced, friendly and constantly evolving start-up environment. Above all, you must be collaborative and patient, with persistence to solve challenging data problems.