The Head of Artificial Intelligence will develop AI models and data tools to support traders with sharper insights and better-informed decision-making. This is a strategic yet hands-on role, working closely with the trading desk and senior leadership. The successful candidate will have a strong commercial mindset and experience in AI, data science, or related fields.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Head of Artificial Intelligence (Global Commodity Trading Firm - Relocation to Singapore)
Our client is a global energy trading, shipping, and logistics group seeking to build its artificial intelligence capability from the ground up. The organization is looking to appoint a commercially minded Chief Artificial Intelligence Officer to develop AI models and data tools that support traders with sharper insights and better-informed decision-making.
This is a strategic yet hands-on role, working closely with the trading desk and senior leadership to turn market data, pricing trends, shipping information, supply and demand dynamics, and internal business data into actionable commercial insights.
The successful candidate will play a key role in shaping how AI is used to enhance trading performance, market visibility, risk management, and overall business decision-making.
Key Responsibilities:
- Define and lead the group’s AI strategy, with a focus on trading performance, market intelligence, and commercial decision-making.
- Build the AI capability from scratch, including data infrastructure, models, tools, governance, and team structure.
- Develop proprietary AI models to support traders in analyzing pricing movements, supply and demand trends, freight activity, market signals, and macroeconomic indicators.
- Work closely with traders to understand decision-making processes, identify data gaps, and develop practical AI tools that support daily trading activity.
- Create AI-powered forecasting, scenario analysis, market alert, and decision-support tools for trading and senior management.
- Integrate internal trading, logistics, finance, and operational data with relevant external market data sources.
- Partner with trading, commercial, risk, operations, IT, and senior leadership teams to ensure AI solutions are practical, reliable, and adopted by the business.
- Support risk management through analytics around exposure, volatility, counterparty risk, logistics constraints, and market scenarios.
- Evaluate external data providers, technology partners, and AI vendors, while deciding what should be built internally versus sourced externally.
- Build and lead a high-performing AI and data team covering data science, machine learning, data engineering, and analytics.
- Establish strong data governance, model governance, cybersecurity, and responsible AI practices.
- Track the impact of AI initiatives on trading insights, decision quality, risk management, operational efficiency, and business value.
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Qualifications & Experience:
- Master’s degree or higher in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field.
- 10+ years of experience in AI, data science, machine learning, quantitative analytics, or advanced analytics, with proven leadership experience.
- Strong track record building AI models, data platforms, or analytics solutions from scratch.
- Experience in commodities trading, energy, shipping, financial markets, hedge funds, or other data-intensive commercial environments is highly preferred.
- Strong understanding of predictive modelling, time-series forecasting, market analytics, optimization, and decision-support systems.
- Ability to work closely with traders and senior commercial stakeholders to translate business challenges into practical AI solutions.
- Strong commercial mindset, with the ability to connect AI capability directly to trading performance, risk management, and business value.
- Experience working with large and complex datasets, including internal business data, external market data, pricing data, and shipping or logistics data.
- Strong understanding of data architecture, cloud infrastructure, machine learning operations, and scalable AI deployment.
- Entrepreneurial, hands-on, and comfortable building a new function in a fast-moving commercial environment.
- High standards of confidentiality, governance, and responsible AI usage, particularly around commercially sensitive information.
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