2. Fundamental & Trading Analysis
Maintain and update supply and demand balances for relevant agricultural commodities and contribute to fundamental market analysis.
Monitor domestic and international price movements, trade flows, margins, and other key market indicators, and contribute to price and scenario analysis.
Identify key market drivers, structural trends, uncertainties, and potential risks, and assess their implications for supply and demand, prices, and trading decisions.
Synthesize data, industry intelligence, and stakeholder perspectives to develop independent market views and actionable insights.
Build a solid understanding of agricultural value chains and market mechanisms, and progressively develop analytical frameworks and methodologies that can be reused across different market situations.
3. Team Collaboration & Research Ownership
Maintain close communication with traders and relevant teams, engage in discussions on market developments, and provide analytical input
Take ownership of assigned research topics and projects, driving work from problem definition and analytical design through execution, iterative communication, and delivery of actionable conclusions.
Qualifications
Minimum Qualifications
Intellectual curiosity about agricultural commodity markets, industries, and real-world business dynamics, with a strong motivation to learn continuously.
Strong logical and analytical capability, with the ability to structure complex problems, identify key drivers, synthesize diverse information, and form sound judgments under uncertainty.
Strong learning agility and adaptability, with the ability to incorporate new information, technology, feedback, and changing market conditions into the analytical process.
Strong data literacy and attention to detail, with the ability to work with structured and unstructured information in a rigorous and organized manner.
Clear and effective written and verbal communication skills, with the ability to translate complex analysis into concise and actionable messages.
Ability to work effectively in a collaborative environment and contribute constructively to team outcomes.
Strong sense of ownership, accountability, and execution discipline.
Preferred Qualifications
Academic background in Data Science & AI, Finance, Agricultural Economics, International Trade, Engineering, Science, or other related disciplines.
Familiarity with data analysis, visualization, data processing, and generative AI tools, with the ability to leverage technology to improve research efficiency, organize information, and support analytical workflows.
Relevant internship, project, research, or extracurricular experience in agriculture, commodities, market intelligence, economics, trading, data analysis, or related fields.
