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3 months ago
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Vortexa·3 months ago
3 months ago

Associate Data Analyst - Energy and Freight Markets

Singapore, Singapore, SingaporeFull-timeRemoteMid · 2+ yearsData Analyst

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Apply faster with autofill FREEvortexa uses Workable - autofill it instead of retyping.careers.example.com/applyAutofillingFull namePriya SharmaEmailpriya.sharma@example.comPhone+49 30 1234567LocationBerlGet the extension

About this role

About Vortexa:

Vortexa was founded to solve the immense information gap that exists in the energy industry. By combining massive amounts of 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.

 

With a growing global presence spanning London, Geneva, Singapore, Dubai, New York, and Houston, Vortexa is well-established and continuing to expand its analytical capabilities and client base.

 

The Challenge:

Vortexa is looking for a Data Analyst to join our Data Analysis team, based in our Singapore office. This is a junior role, ideal for a recent graduate with strong analytical instincts or a candidate with up to two years’ experience. You will join a global team headquartered in London.

In this role, your core responsibilities will center on the quality and integrity of Vortexa’s proprietary datasets. You will also support internal and external data queries, including client-facing validation requests routed through our support function, and contribute to data quality initiatives raised by the Analyst team or other teams. You will learn and take ownership of our internal tools and processes to help maintain data excellence on a day-to-day basis, and over time help to develop and refine those tools and processes.

You will work closely with experienced data and market analysts across our global team, collaborating on data quality initiatives and presenting your findings. You will also work in close collaboration with our R&D team, helping to identify patterns of systematic data errors that can be escalated for longer-term engineering fixes. You will be encouraged to propose more systematic solutions to problems that are currently being addressed manually, leveraging scripting skills in Python and/or Excel and leveraging AI tools such as Claude to enhance the efficiency and quality of your work.

You must be highly analytical, detail-oriented and be genuinely curious about data. Motivated to investigate and understand why something looks wrong, not just flagging it. You need to be a driven self-starter capable of working independently as well as collaboratively depending on the task at hand, and comfortable operating as part of a small local team embedded within a larger global organisation. Above all, you must be inquisitive, patient, and persistent when it comes to solving challenging data problems.

Key Responsibilities:

●      Take ownership of daily data quality processes, including structured data checks and quality control routines across Vortexa’s proprietary datasets.

●      Investigate data issues, whether raised through internal channels, client support queries, or your own observations.

●      Diagnose root causes and apply fixes to resolve them.

●      Map and reconcile data between Vortexa’s internal datasets and external data sources or third-party providers.

●      Handle internal and external support requests, helping clients and colleagues validate data and understand discrepancies.

●      Collaborate with the R&D team to surface patterns of systematic data errors and contribute to longer-term data improvements.

●      Write and maintain Python scripts to support data investigations and automate routine tasks, along with a willingness to leverage AI tools to enhance your work.

●      Proactively identify opportunities to improve or systematise manual processes, (with AI or scripting), and contribute ideas to the broader data analysis team.

Requirements

You Have:

●      A degree-level education and/or experience working in a quantitative, scientific, or analytical discipline (economics, mathematics, computer science, engineering, geography or similar).

●      Strong numeracy, analytical and computer skills with a genuine interest in working with data.

●      Working knowledge of Python. Not at a software engineering level, but sufficient to write, adapt and validate scripts for data investigation and automation tasks.

●      An active interest in AI tools and their practical application to data analysis and investigative workflows.

●      Strong attention to detail, with the ability to manage and prioritise multiple tasks simultaneously.

●      Strong communication skills, (written, verbal, and listening), with the confidence to work across a global, cross-functional team.

●      Problem-solving as a core character trait – someone who is motivated to find a root cause and see a fix through to completion.

 

Nice to Have:

●      Some background in, or genuine curiosity about, the oil and gas or shipping industries; an understanding of basic energy market concepts is an advantage.

●      Familiarity with SQL – basic SQL is sufficient for many routine tasks; more advanced query writing is helpful for complex investigations.

Benefits

  • Stock-options in a fast-growing, high-potential business
  • An open, collaborative, and supportive working culture built on merit, which celebrates creative thinking and “getting things done.”
  • The opportunity to work with AI-driven technology in a scale-up environment with commodity trading experts
  • Private Health Insurance offered via AXA
  • A flexible working policy- accommodating both remote & home working, with regular staff events
  • Global Volunteering Policy to help you ‘do good’ and feel better

Company

Vortexa
Singapore, Singapore, Singapore

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from Vortexa's careers site·first seen 23 Jun 2026·last verified 8 Sept 2026·How we source jobs

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