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Market Data Analyst Metals & Minerals

Organismo
Kpler
País
🇬🇧 Reino Unido
Lugar
United Kingdom
Puestos
1
Tipo de vínculo
privado

Descripción del puesto

At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors. Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 700 experts from 35+ countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success. Your future position: Kpler’s Dry Bulk business unit is expanding its footprint in the Metals & Minerals sector. We are looking for a Market Data Analyst to take ownership of data quality and operational processes across ferrous and non-ferrous metals, solid fuels, and industrial minerals. This is a role for someone who wants to sit close to how global commodity markets actually move. You will combine strong SQL and Python skills with a curiosity about the real-world events shaping those movements - from shifting trade flows and supply chain disruptions to changes in industrial demand, policy, and pricing dynamics. You won’t just be processing data. You will play a key role in turning complex, high-volume datasets into reliable market intelligence used by clients to understand what is happening in global physical markets. Your work will directly influence how accurately we reflect real-world commodity flows. As the team grows, you will also help mentor junior analysts and act as a bridge between raw data, market developments, and the insights our clients depend on to make decisions. Your mission is to: Take charge of specific regions and product groups, ensuring the highest standard of data quality by reviewing internal constraints, validating automated outputs, and ingesting data from diver

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