Python Developer

Vitol
London
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning/Python Developer

Data Science Quant Python - Fintech

Experienced Recruitment Consultant – Artificial Intelligence & Bio Artificial Intelligence Manchester (Hybrid)

Machine Learning Engineer

Data Scientist

Senior Machine Learning Engineer, Search & Recommendations

Company Description

Vitol is a leader in the energy sector with a presence across the spectrum: from oil through to power, renewables and carbon. From 40 offices worldwide, we seek to add value across the energy supply chain, including deploying our scale and market understanding to help facilitate the energy transition. To date, we have committed over $2 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world.

Our people are our business. Talent is precious to us and we create an environment in which individuals can reach their full potential, unhindered by hierarchy. Our team comprises more than 65 nationalities and we are committed to developing and sustaining a diverse work force. Learn more about us here.

Job Description

We are looking for a talented and motivated Python developer to work within our Vitol’s 
MIS department and work closely on various initiatives and as well as with our business dev community. In this role you will leverage technology, data and automation to support Vitol’s fast paced business model and enable rapid adaption to upcoming opportunities. Having a basic understanding of the business domain you will be engaged in a variety of tasks along the development stack, from expanding internal packages, tailoring applications to collaborating/liaising with the central development and data science teams on the core platform.

What you’ll do 

Working with EU business sponsors to drive out requirements for data ingestion and access Contribute and help drive business development efforts including standardization and consolidation of core modules Writing modular, reusable components to liaise between external sources of data, internal tools and databases Maintaining the cleanliness and centrality of the Vitol Python core codebase Efficiently coordinate with other team members in the Houston office Help lead and organize policies related to our Vitol python development community and act as a liaison for our growing business development efforts

Qualifications

2 to 6 years of enterprise-level coding experience with Python in Linux environment  Oracle / PL SQL development experience including queries and stored procedures Strong understating of object-oriented design, design patterns, SOA architectures Familiarity with Pandas and NumPy packages Commodities/Energy Industry experience strongly desired Familiarity with containerization solutions like Docker and Kubernetes is a plus Proficient understanding of peer-reviewing, code versioning, and bug/issue tracking tools Awareness of continuous integration and delivery concepts/technologies Experience working in an agile scrum development model Strong communication skills (written and verbal) Computer Science, MIS or related degree

Additional Information

Personal Characteristics

Team player Self-motivated with the ability to prioritize, meet deadlines, and manage changing priorities Able to work in a high pressure on-call environment with changing priorities Proactive and customer focused “make it work” mentality Highly responsive, energetic and enthusiastic Resourceful and able to think creatively and adapt

What we offer 

Large variety of projects, creative freedom and direct access to our user community This job operates in a professional office environment  Central location close to Victoria Station Potential for travel to our Singapore, Houston and Geneva offices Modern well-equipped gym

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

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

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.