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 600 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.
The Cargo Models team is responsible for building highly accurate cargo tracking models to provide live insights on trade details in the maritime transport industry. A wide range of efficient exact and approximated Operations Research / Data Science techniques are used to process and transform live data and inject them into different data pipelines. Cargo Models team is directly responsible for the quality of final outputs provided to the client, making it an important product for Kpler.
Your objective:
Based on a multitude of sources, we are trying to track cargoes carried in thousands of vessels each day. For each vessel, we first compute her track, compositions exchanged in each port. By building an accurate model per vessel, we can construct a highly precise live image of the maritime transport world represented by trades and flows.
This can be challenging as vessels are linked with each other through ship-to-ship operations, which implies that compositions should be computed on sets of vessels of different sizes. Moreover, on vessel level, compositions are interconnected through physical constraints.
Currently, the problem is solved in two steps. First, we compute overall quantities loaded/discharged between different vessels. Secondly, we compute compositions vessel by vessel. This is a simplification as there is a strong dependency between vessel behaviors and their compositions.
The objective of the internship is to first, enrich the current quantity model to take into account compositions dynamics and business rules. As this will negatively impact the performance of the current pipeline, the second step of the internship will focus on enhancing performance of the new model by testing some decomposition techniques as the problem presents a nice block-structure.
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