Junior Market Data Analyst – Chartering

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 Join Kpler’s Chartering team as a Junior Market Data Analyst – Chartering and play a key role in ensuring the quality and accuracy of the data that powers our Chartering products. Kpler’s Chartering products rely on accurate vessel, ownership and market data to help charterers, shipowners and brokers make informed commercial decisions. In this role, you will work hands-on with the datasets behind these products, investigating inconsistencies, validating information and helping improve data quality at scale. Your work will span a range of chartering datasets, from vessel ownership and characteristics to fixtures, cargo orders, vessel positions and shipping zones. You will use SQL and Python to extract, transform and analyse data, build validation checks and investigate potential issues.  This is a role for someone who enjoys getting into the detail of data, asking why something doesn't look right and finding ways to identify and solve problems systematically. You will work closely with Product, Data, Research, Engineering and AI/ML teams, turning individual data issues into broader improvements across Kpler's datasets and products. Your mission is to: Monitor, validate and improve the quality of key datasets supporting Kpler's Chartering products. Investigate data gaps,