Base metals Analyst

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The Analyst will report to the Manager of Metals demand for Europe and the Americas. The role will focus primarily on market outlooks for both the short and long term and on the demand-side aspects across base metals, particularly aluminum.


This analyst will be involved in the design and development of new methodologies, quantitative models, and fundamental analysis and commentary (as relevant) that enhance existing or new products and services. The work will include maintenance of some of the existing data suites, while contributing written, graphical and numerical work to the range of GFMS' metals research products and developing fresh initiatives and products. This is a pro-active team and the ideal candidate will have a flair for innovation and be prepared also to work with various departments in the Supply Chain Commodities Research Division and potentially the Advisory and Investment Management team in order to grow new ideas and expand the scope of existing products. In particular this will be playing a role in expanding our coverage of the automotive sector.

Skills and experience

Strong numerical, written and verbal skills in order to be able to assemble and analyse the data captured and to articulate the findings through written research reports and presentations as well as conversations and consultation with clients, prospects and market stakeholders. At a personal level, the qualities required would be a confident, resourceful self-starter, plus a mind geared to rigorous attention to detail and a good team spirit.

Fully conversant with Excel, Word, Power Point; the Adobe suite of products would also be highly advantageous.

Preferred skills and experience

Solid work in the field of commodity research, especially the metals sector, or in an associated consuming industrial sector, particularly automotive or processing areas such as the chemical industry.

Knowledge of languages other than English, and of statistical techniques would be an advantage, but are not essential. A logical approach to data manipulation and putting information into context would be highly advantageous.

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