Quantitative Analyst: Production Models for Energy Trading

Nitor Energy; Denmark; On-site; DKK 600,000 - 900,000; Full time

Benefits offered by this job

Young, dynamic, ambitious environment

Career development and growth

Weekly sports activities and events

Lunch arrangement in canteen

Office in Aarhus center

Job summary

Nitor Energy is a fast‑growing energy trading company seeking a Quantitative Analyst to shape models, algorithms and decision‑making at the center of our trading desk. You will work with data, code and complex market dynamics to build production‑ready solutions that impact trading decisions daily.

You’ll collaborate with traders, develop quantitative models, improve analytics and risk tools, and contribute to scaling our data infrastructure, with a pragmatic, ownership‑driven mindset and a

Qualifications

• Master's degree in a quantitative field.
• Strong numerical, analytical and problem-solving skills.
• Good Python knowledge and eagerness to code; other languages a plus.
• Excellent teamwork and a pragmatic, result-driven mindset.

Responsibilities

• Work with traders to develop and refine quantitative models.
• Improve workflows, analytics, risk tools and business processes.
• Perform ad hoc analyses to support trading, risk, and decisions.
• Design and maintain analytic views for monitoring strategies.
• Support development and maintenance of Python-based models.
• Help scale data infrastructure.

Skills

Python

Quantitative skills

Analytical mindset

Team player

Coding eagerness

Education

Master's degree in quantitative field

Tools

Python

Job description

Nitor Energy is a fast‑growing energy trading company seeking a Quantitative Analyst to shape models, algorithms and decision‑making at the center of our trading desk. You will work with data, code and complex market dynamics to build production‑ready solutions that impact trading decisions daily.

You’ll collaborate with traders, develop quantitative models, improve analytics and risk tools, and contribute to scaling our data infrastructure, with a pragmatic, ownership‑driven mindset and a