Role Summary Build and maintain data-driven end-use and 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 placement, infrastructure, data centric 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. - Analyze capacity across end-use sectors to consume scrap vs. refined metals. Data Integration & Monitoring: - Build scalable data pipelines integration national statistics, industry data, company disclosures, and alternative data (e.g., shipping, and satellite). - Generate model outputs with dynamic and real-time, high-frequency integration. - Develop dashboards presenting key indicators in clear, actionable format. Market Analysis & Insights: - Identify inefficiencies and relative value opportunities across commodities and regions. - Perform scenario analysis with macro, policy, and geopolitical factors. - Support trading and portfolio positioning with timely, data-driven insights. Requirements: Experience & Knowledge: - 5+ years experience in metals/commodity research, with close working with 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 (model development, pipelines), strong SQL, experience with large-scale multi-source datasets and real-time systems. Other Skills: - Strong analytical and problem-solving ability. - Ability to operate in a fast-paced, collaborative environment. - Excellent communication (written and verbal, English).

Downstream Demand Analyst (Metals)