What actually is systematic trading and the capabilities behind it? How can systematic trading generate returns? How can it inform trading desks and an organisation’s decision-making? Why is it delivering a competitive advantage and strategic edge to companies in the energy and commodities sector? What developments have shaped this space in recent years, and how is systematic trading influencing global markets today?
In this episode of the HC Commodities Podcast, host Paul Chapman speaks with Hans Balgobin, an experienced systematic trader who has built trading platforms in both equities and energy with HSBC, Shell and Millennium, and who is now joining Uniper in a systematic trading role.
Read below for the five key talent impacts shaping systematic trading in energy and commodities.
Key Talent Impacts
1. Why is systematic and quantitative expertise now essential in energy and commodities trading?
Energy and commodities firms are rapidly adopting systematic trading models to improve decision-making and risk management. This creates a surge in demand for talent with quantitative skills—such as data science, coding, and algorithmic modelling—combined with practical trading experience. Professionals able to design and deploy repeatable, rule-based strategies are becoming essential.
2. How does data engineering and analytics shape the future of trading performance?
High-quality, real-time data is now the backbone of trading in energy markets. Organisations need data engineers and analysts who can source, clean, and process market feeds, weather forecasts, shipping data, and asset information. Without this infrastructure, AI-driven and systematic trading systems cannot operate effectively.
3. What is the value of combining deep market expertise with advanced modelling?
Deep knowledge of commodity markets—such as energy flows, regulatory frameworks, and physical constraints—remains a vital differentiator. The most valuable professionals combine domain expertise with quantitative and AI-driven approaches, ensuring models are grounded in reality and not vulnerable to overfitting or blind assumptions.
4. Why are compliance and governance capabilities critical in algorithmic trading?
With regulators closely monitoring algorithmic and high-frequency trading, firms must build strong compliance and risk management capabilities. Talent is required that can design transparent, auditable systems, manage algorithmic execution rules, and communicate effectively with boards and regulators.
5. How are hybrid, cross-functional teams redefining trading talent in the energy sector?
The future of energy and commodities trading depends on multidisciplinary teams. Systematic trading functions increasingly combine data scientists, quant developers, market analysts, compliance experts, and traders. Leadership that can integrate these skills into a unified capability is a competitive advantage in a sector undergoing rapid digital and AI-driven transformation.
HC Group is a global search firm dedicated to the energy and commodities markets.
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HC Commodities Podcast Briefing
Edited highlights and themes from the podcast episode.
Why is systematic and quantitative expertise now essential in energy and commodities trading?
Systematic trading has shifted from equities into commodities, becoming a strategic capability. Firms need professionals who can design rule-based, repeatable strategies using coding, data science, and quantitative analysis. In energy markets where liquidity, volatility, and complexity are high, these skills deliver clarity and consistency in decision-making.
How does data engineering and analytics shape the future of trading performance?
Data is the foundation of modern energy trading. Engineers and analysts are required to source, clean, and monitor diverse inputs—ranging from market prices to weather models, shipping data, and asset flows. Without this robust data infrastructure, AI models and systematic strategies cannot function effectively.
What is the value of combining market expertise with advanced modelling?
Domain knowledge remains a competitive advantage. Understanding physical supply chains, regulatory frameworks, and behavioural market drivers helps prevent overfitting and strengthens the interpretation of signals. The most effective professionals bridge traditional trading experience with quantitative modelling.
Why are compliance and governance capabilities critical in algorithmic trading?
As algorithmic and high-frequency trading expands into commodities, regulatory oversight has intensified. Traders and developers must design transparent, auditable systems that meet strict execution, order-size, and risk management requirements. Talent with compliance and governance expertise ensures systematic desks operate responsibly and sustainably.
How are hybrid, cross-functional teams redefining trading talent in the energy sector?
The future lies in multidisciplinary teams that combine data scientists, quant developers, compliance experts, and experienced traders. Leaders who can integrate these diverse skills are best placed to capture opportunities, manage risks, and shape the next phase of AI-driven trading in the energy and commodities sector.