Quantitative Trading Analyst

Charles Levick Limited; Hamburg; Hybrid; EUR 50.000 - 70.000; Vollzeit

Zusammenfassung

A prominent trading firm is looking for an analytical mind to build and enhance trading models in high-frequency energy markets. The successful candidate will work with a collaborative team in Hamburg, using innovative approaches to interpret data and influence trading strategies. This role offers a unique opportunity to excel in a dynamic, high-impact environment focusing on real-time market challenges.

Qualifikationen

• Strong grasp of linear algebra, calculus, and optimisation.
• Solid foundation in probability and stochastic modelling.
• Familiarity with modern machine learning approaches.

Aufgaben

• Build predictive models using statistical and machine learning approaches.
• Collaborate with developers and traders to evolve trading strategies.
• React to changing market conditions for real-time decision-making.

Kenntnisse

Mathematical skills

Programming (Python)

Data interpretation

Statistical analysis

Machine learning

Agile practices

Jobbeschreibung

We’re looking for a sharp, analytical mind to join a team at the forefront of real-time electricity markets. If you're skilled in math, programming, and data interpretation, and curious about the challenges of fast-paced energy trading, this opportunity may be the right fit for you.

In this role, you'll contribute to designing and refining trading models that respond to rapid market fluctuations. You'll be immersed in an environment where your insights directly influence trading outcomes. Your day-to-day will involve building and improving algorithms, interpreting market signals, and uncovering inefficiencies through data-driven methods.

You’ll be based in Hamburg, with flexibility for hybrid work. The team culture is informal and collaborative, and the work is hands-on, high-impact, and constantly evolving.

What you’ll be doing :

• Build and enhance predictive models using statistical and machine learning approaches.
• Work with large datasets to identify recurring patterns and short-term market anomalies.
• Collaborate closely with fellow developers, researchers, and traders to evolve trading strategies.
• React to changing market conditions and contribute to real-time decision-making.

What you bring :

• Strong grasp of core mathematical areas like linear algebra, calculus, and optimisation.
• Solid foundation in probability, stochastic modelling, statistical inference, and time series analysis.
• Familiarity with modern machine learning approaches (e.g., deep learning, ensemble methods).
• Proficiency in Python; additional experience with R or C++ is an asset.
• Experience working with Agile practices, version control, and software deployment pipelines.
• Bonus) Exposure to electricity or commodities markets, particularly intraday or real-time trading.
• Bonus) Understanding of order book dynamics and short-term market behaviour.
• Background in handling real-world time series data for forecasting or pattern recognition.

What you’ll learn :

• Deep expertise in the mechanics of European power markets.
• How to manage and execute strategies in high-frequency, high-risk trading environments.
• Methods to evaluate trade-offs between risk and reward in volatile settings.
• How to take ownership of strategies and operate them with confidence in live market conditions.