Gas Trading Quantitative Researcher | AI-Driven Models

Cph Ai Hub; Aarhus; Hybrid; DKK 900,000 - 1,300,000; Full time

Benefits offered by this job

Competitive benefits

Opportunity to grow with the company

Chance to become partner

Flat organization

International environment

Job summary

MFT Energy in Aarhus seeks a Quantitative Researcher to join our gas trading team, blending math, coding, and market insight to turn ideas into trading strategies. You’ll collaborate with traders, researchers and engineers in a fast, feedback-driven environment.

You’ll build and backtest models, develop Python-based tools, and translate complex market data into actionable insights. We value curiosity, teamwork and ownership, with opportunities to influence live trading and shape future solutions.

Qualifications

• Strong mathematical and programming skills.
• Experience with energy markets or quantitative trading is a plus.
• Fluent in English.

Responsibilities

• Develop and improve quantitative models and market forecasts that support trading decisions
• Work closely with traders and researchers to identify, analyse and evaluate market opportunities
• Design, develop and maintain Python-based tools and models
• Research, backtest and evaluate trading ideas and strategies
• Transform complex market data into practical insights and actionable solutions
• Use AI tools to speed up development, research and problem-solving
• Continuously improve existing models, systems and processes based on feedback and performance
• Take ownership of your work from initial idea through implementation and ongoing improvement

Skills

Quantitative background

Python programming

Statistical analysis

AI interest

Team collaboration

Education

Mathematics/Physics/Engineering background

Tools

Python

Pandas

Job description

MFT Energy in Aarhus seeks a Quantitative Researcher to join our gas trading team, blending math, coding, and market insight to turn ideas into trading strategies. You’ll collaborate with traders, researchers and engineers in a fast, feedback-driven environment.

You’ll build and backtest models, develop Python-based tools, and translate complex market data into actionable insights. We value curiosity, teamwork and ownership, with opportunities to influence live trading and shape future solutions.