Qube Research & Technologies
Downstream Demand Analyst (Metals)
Shanghai · Work style not stated
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About the role
Description from the employer’s posting. Check the employer’s page for the current version.
- EmployerQube Research & Technologies
- LocationShanghai
- Work styleWork style not stated
- Employer posted
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
- 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).
- Conduct intensity analysis and forward demand projections, adjusting for cyclical effects (e.g. demand destruction vs deferral).
- Track inventories across the value chain using semi-finished and end-use data.
- 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).
- Generate model outputs programmatically, incorporating real-time and high-frequency macro data.
- Develop dashboards to present key high-frequency indicators in a clear, actionable format.
- Market Analysis & Insights
- Identify market inefficiencies and relative value opportunities across commodities and regions.
- Perform scenario analysis incorporating macro, policy, and geopolitical factors.
- Support trading and portfolio positioning with timely, data-driven insights.
Key Requirements
Experience & Knowledge
- 5+ years’ experience in metals/commodity research, with strong focus on first-use and end-use demand.
- Deep understanding of downstream sectors and global metals value chains.
- Familiarity with scrap markets, trade flows, and industry dynamics.
Technical Skills
- Advanced Python programming (model development, data pipelines).
- Strong SQL proficiency.
- Experience working with large, multi-source datasets and real-time data systems.
Other Skills
- Strong analytical and problem-solving capabilities.
- Ability to operate in a fast-paced, collaborative environment.
- Excellent communication skills (written and verbal, English).
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Skills in this posting
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