Intraday Power Quant Trader

SEFE MARKETING & TRADING SINGAPORE PTE. LIMITED; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading trading firm in Singapore seeks an Intraday Power Quant Trader to develop and optimize trading strategies in European power markets. You will work with fundamental traders and quantitative models to maximize trading efficiency and profit. A strong background in quantitative analysis and programming in Python or C++ is essential. This role offers dynamic responsibilities, including building execution algorithms and improving trading decision models.

Qualifications

• Strong background in quantitative analysis, trading strategy development, or algorithmic execution.
• Excellent understanding of the European power market fundamentals.
• Proven ability to design, code, and implement trading algorithms.

Responsibilities

• Design and maintain forecasting and pricing models to support trading decisions.
• Build, automate, and optimize execution algorithms to maximize trading efficiency.
• Develop and maintain robust analytics tools for trade idea generation and post-trade analysis.

Skills

Quantitative analysis

Trading strategy development

Algorithmic execution

Python programming

C++ programming

Statistical model validation

Education

Degree in a technical field (Mathematics, Physics, Engineering, Computer Science, Quantitative Finance)

Job description

As an Intraday Power Quant Trader at SEFE, you will sit at the intersection of quantitative modelling and real-time trading, developing, executing, and optimizing trading strategies across the European intraday power markets. You will work hand-in-hand with fundamental intraday traders, combining quantitative techniques with fundamental market insights to identify and capture trading opportunities, optimizing both price and volume execution. You will also oversee the optimisation of SEFE power asset fleets across Europe.

What You Will Do

As an Intraday Power Quant Trader you will develop and deploy data-driven trading strategies in European short-term power markets, leveraging both systematic models and discretionary insights from fundamental traders. You will also collaborate continuously with discretionary power traders to interpret market conditions, align on trading themes, and integrate real-time intelligence into quantitative models.

• Design and maintain forecasting and pricing models (short-term fundamentals, flow-based dispatch, asset behaviour, etc.) to support intraday trading decisions.
• Build, automate, and optimize execution algorithms to maximize trading efficiency and P&L.
• Develop and maintain robust analytics tools to enhance market visibility, trade idea generation, and post-trade analysis. Analyse, back-test, and refine strategies using historical and real-time market data.
• Contribute to the optimization of SEFE’s power asset fleet, leveraging both operational constraints and market arbitrage opportunities to create value to our customers.
• Partner with operations and technology teams to continuously enhance infrastructure, data pipelines, and strategy deployment capabilities.
• Monitor and interpret European power market news, regulatory updates, and infrastructure developments, translating these into actionable quantitative insights.

What You Will Bring

You will have a strong background in quantitative analysis, trading strategy development, or algorithmic execution, ideally in power, commodities, or short-term markets. Excellent understanding of the European power market fundamentals, including generation, transmission, balancing mechanisms, and market rules is essential. You will also have:

• Proven ability to design, code, and implement trading algorithms, with expertise in Python, C++ and other performant languages a plus.
• Familiarity with Stack, Delta models, load forecasting, or other power-specific models is highly advantageous.
• Strong analytical mindset with the ability to blend structured quantitative approaches with real-time discretionary trading inputs.
• Experience with backtesting frameworks and statistical model validation techniques.
• Ability to communicate complex technical concepts to both technical and non-technical stakeholders.
• Degree in a technical field (e.g., Mathematics, Physics, Engineering, Computer Science, Quantitative Finance) or equivalent practical experience.