Role Summary
Build and maintain data-driven end-use demand models across global metals markets, translating sector-level insights into actionable views for trading and investment.
Core Responsibilities
- Demand Modelling
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Develop bottom-up end-use demand models (starting with China, then globally and covering major regional markets) across key sectors (e.g. real estate, transportation, power generation and distribution, infrastructure, data centres / AI, appliances).
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Conduct intensity analysis and forward demand projections, adjusting for cyclical effects (e.g. demand destruction vs deferral).
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Track inventories across the value chain using semi-finished and end-use data.
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Analyse capacity across end-use sectors to consume scrap vs refined metals.
- Data Integration & Monitoring
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Build scalable data pipelines integrating national statistics, industry data, company disclosures, and alternative data (e.g. shipping, customs, satellite).
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Generate model outputs programmatically, incorporating real-time and high-frequency macro data.
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Develop dashboards to present key high-frequency indicators in a clear, actionable format.
- Market Analysis & Insights
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Identify market inefficiencies and relative value opportunities across commodities and regions.
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Perform scenario analysis incorporating macro, policy, and geopolitical factors.
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Support trading and portfolio positioning with timely, data-driven insights.
Key Requirements
Experience & Knowledge
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5+ years’ experience in metals/commodity research, with strong focus on first-use and end-use demand.
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Deep understanding of downstream sectors and global metals value chains.
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Familiarity with scrap markets, trade flows, and industry dynamics.
Technical Skills
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Advanced Python programming (model development, data pipelines).
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Strong SQL proficiency.
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Experience working with large, multi-source datasets and real-time data systems.
Other Skills
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Strong analytical and problem-solving capabilities.
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Ability to operate in a fast-paced, collaborative environment.
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Excellent communication skills (written and verbal, English).