Associate Data Analyst - Energy and Freight Markets

Vortexa
London
11 months ago
Applications closed

Related Jobs

View all jobs

Associate Data Analyst

Associate Data Analyst

Associate Data Analyst - Finance Data, Hybrid (Glasgow)

Hybrid Data Analyst: Financial Markets & Data Insight

Senior Data Engineer

Senior Data Engineer

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.  

Requirements

You have... 

  • Recently graduated and/or and 1-2 years' experience in analysing and investigating datasets 
  • Advanced numeracy, analytical and computer skills for data analysis, manipulation and management.  
  • Experience working with advanced Excel, SQL and ideally Python. Working knowledge of GIS tools a plus. 
  • A results oriented focus, strong attention to the detail and the ability to efficiently prioritise multiple objectives 
  • A keen interest in learning and solving problems critical to the future of energy and shipping markets. Experience in commodities/energy and shipping is a bonus.  
  • Strong communication skills; written, verbal and listening 
  • A collaborative mindset, working with a range of different teams and diverse skillsets across the company

Benefits

  • A vibrant, diverse company pushing ourselves and the technology to deliver beyond the cutting edge
  • A team of motivated characters and top minds striving to be the best at what we do at all times
  • Constantly learning and exploring new tools and technologies
  • Acting as company owners (all Vortexa staff have equity options)– in a business-savvy and responsible way
  • Motivated by being collaborative, working and achieving together
  • A flexible working policy- accommodating both remote & home working, with regular staff events
  • Private Health Insurance offered via Vitality to help you look after your physical health
  • Global Volunteering Policy to help you ‘do good’ and feel better

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.