Commodities Quant Researcher

Carter Wahlberg; Greater London; Hybrid; GBP 80,000 - 140,000; Full time

Job summary

Major Energy Trading House in London seeks a Commodities Quant Researcher to develop and run systematic signals across oil, gas, metals and refined products. You will own the research-to-production cycle, collaborating with senior traders and quants to deploy models that feed directly into live trading.

The role emphasizes building your own Python-based research stack, stress testing, and performance attribution.

Qualifications

• 3-5 years in a systematic quantitative research or trading role (hedge fund, prop shop, bank or major physical merchant).
• Exposure to at least two of: oil & products, gas, metals; cross-commodity experience is a strong plus.
• Strong Python and SQL, comfortable in at least one OO language; build your own tools.
• Solid grasp of time-series modelling, statistical learning and portfolio/risk concepts; translate domain expertise into P&L-generating ideas.
• Based in London or willing to relocate; on-site presence is preferred to work closely with the trading desk.

Responsibilities

• Develop original quantitative signals and systematic strategies across oil, refined products, gas and metals.
• Own the full research‑to‑production cycle: idea generation, backtesting, stress testing, cost/slippage modelling and live deployment.
• Work closely with senior traders and quants on research direction, portfolio construction and risk management; contribute to business‑management discussions as the book grows.
• Build and maintain your own research stack in Python and collaborate with quant developers to productionise code.
• Monitor live strategies, exposures and P&L, and iterate models based on performance attribution and changing market structure.

Skills

Python

SQL

Time-series modelling

Statistical learning

Portfolio/risk concepts

Job description

Commodities Quant Researcher (Oil, Metals, Gas)

Major Energy Trading House - London (On-site / Hybrid)

A leading global energy and commodities trading house is expanding its systematic trading capability within a well‑established proprietary trading desk. The team runs a diversified book across oil, refined products, gas, power and metals, and is now building out a more model‑driven, systematic sleeve alongside its core fundamental and relative‑value strategies.

This is a high‑ownership seat: you will research, build and run systematic strategies end‑to‑end, with your signals feeding directly into live trading. The platform (data, backtesting, execution, risk) is already in place; your job is to generate alpha, not to rebuild infrastructure. Well‑built strategies translate straight into P&L, and the people who build them are the ones who run them.

YOUR ROLE:

• Develop original quantitative signals and systematic strategies across oil, refined products, gas and metals, using market data plus fundamental/alternative datasets (inventories, flows, weather, positioning, text, etc.)
• Own the full research‑to‑production cycle: idea generation, backtesting, stress testing, cost/slippage modelling and live deployment.
• Work closely with senior traders and quants on research direction, portfolio construction and risk management; contribute to business‑management discussions as the systematic book grows.
• Build and maintain your own research stack in Python (data pipelines, feature engineering, backtesting, signal monitoring) and collaborate with quant developers to productionise code.
• Monitor live strategies, exposures and P&L, and iterate models based on performance attribution and changing market structure.

YOUR PROFILE:

• 3-5 years in a systematic quantitative research or trading role (hedge fund, prop shop, bank or major physical merchant), with a genuine signal‑generation track record.
• Exposure to at least two of: oil & products, gas, metals; cross‑commodity experience is a strong plus.
• Strong Python and SQL, comfortable in at least one OO language; able to build your own tools rather than wait for them.
• Solid grasp of time‑series modelling, statistical learning and portfolio/risk concepts; experience turning domain expertise into P&L‑generating trade ideas.
• Based in London or willing to relocate; on‑site presence is preferred to work closely with the trading desk.

What’s on offer

• Direct line from your models to live trading and P&L; discretion is reserved for genuine market dislocations, not second‑guessing signals.
• Access to extensive market data, fundamental research and physical market insight across oil, gas, power and metals.
• Experienced team of quants, traders and engineers who’ve already built the core infrastructure; you focus on alpha, not plumbing.
• Competitive compensation with meaningful upside tied to the performance of the strategies you build.