Structured Derivatives Sales (commodities)

Redstone Search Group
London
10 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Data Scientist KTP Associate

Data Scientist KTP Associate - Salford

Data Scientist

Data Scientist

Redstone Commodity Search focus on offering 360° search solutions to the global commodities markets. With a competitive coverage of Trading Houses, Producers, Majors, Utilities, Merchants, Hedge Funds, Investment Banks and Brokerages; Redstone Commodity Search can confidently offer you an edge in today’s volatile market.


Redstone Commodity Search are working with a renewable energy and risk management trading firm looking to onboard a structured derivatives sales, to be based in London.


Key Responsibilities:


  • Origination & Sales:Develop and maintain client relationships, identifying opportunities for structured transactions and risk management solutions.
  • Structuring & Execution:Lead the structuring and negotiation of OTC derivatives, including swaps, options, and forwards, ensuring seamless execution.
  • Market Intelligence:Provide insights on market trends, regulatory developments, and price risks across oil, gas, power, carbon, renewables, and agricultural products.
  • Solution Design:Collaborate with clients to create tailored risk management and financing solutions.
  • Risk Management:Work with trading and risk teams to ensure solutions align with internal policies and market conditions.
  • Cross-Selling:Identify opportunities across the company’s product suite, including financing solutions and physical supply.
  • Client Development:Expand presence through business development, networking, and industry participation.


Key responsibilities:


  • Strong commodities knowledge in a front-office environment, particularly in energy and commodities, ideally from a bank or from an investment fund.
  • 5+ years of experience in origination and negotiation of structured derivative transactions. Experience in structuring is a plus.
  • Familiarity with European energy & environmental regulations, with experience in agri, soft commodities, and FX being advantageous.
  • Strong analytical skills and market interpretation capabilities.
  • Excellent communication and relationship management skills.
  • Detail-oriented with the ability to manage multiple priorities.

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.