ML-Driven Quant for 24/7 Short-Term Trading

Danske Commodities; Denmark; Hybrid; DKK 800,000 - 1,200,000; Full time

Benefits offered by this job

Flexible work life

Home setup covered

Top-tier parental leave

Unlimited paid child's sick days

New HQ in Aarhus

Job summary

Danske Commodities seeks a highly skilled quantitative ML engineer to design and deploy machine learning driven trading strategies. You will work with Python to transform large datasets into actionable signals and predictive models, while continuously improving models, infrastructure, and research processes.

Collaboration with traders and analysts is essential to translate market insights into scalable quantitative solutions.

Qualifications

• Hold an MSc or PhD in data science, computer science, mathematics, physics, or a related field.
• Advanced Python developer with experience building production-quality code.
• Extensive experience with ML techniques and frameworks (PyTorch, Scikit-learn).
• Keep up with the latest ML/deep learning innovations and translate cutting-edge research into practical solutions.

Responsibilities

• Design, develop, and deploy ML-driven trading strategies using Python.
• Transform large-scale and high-dimensional datasets into actionable trading signals and predictive models.
• Continuously improve existing models, infrastructure, and research processes to maintain a competitive edge.
• Collaborate closely with traders and analysts to translate market insights into scalable quantitative solutions.
• Take ownership of bringing new ideas into production.

Skills

Python

Machine Learning

Deep Learning

Education

MSc/PhD in data science or related field

Tools

PyTorch

Scikit-learn

Job description

Danske Commodities seeks a highly skilled quantitative ML engineer to design and deploy machine learning driven trading strategies. You will work with Python to transform large datasets into actionable signals and predictive models, while continuously improving models, infrastructure, and research processes.

Collaboration with traders and analysts is essential to translate market insights into scalable quantitative solutions.