Description
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 500 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.
More specifically, you will be asked to:
- Enrich the existing volume model (MILP) with composition constraints
- Conduct a literature review on decomposition techniques applicable in this context
- Implement the initial model and experiment its efficiency
- Evaluate and iterate on the performance of some decomposition techniques, considering real-world constraints and operational challenges
Qualifications:
- Currently pursuing a Master’s degree in Applied mathematics, Computer Science, or a related field.
- Strong background in optimization techniques, algorithms and mathematical modeling.
- Practical knowledge of Python and SQL
- Ability to work independently and collaboratively within a dynamic team environment.
- Understands software industry practices and are ready to acquire them.
- Fluent English speaker.
What we offer
- Hands-on experience solving a real-world optimization problem with significant industry impact.
- Mentorship from experienced professionals in the optimization and computer science sectors.
- Exposure to cutting-edge technologies and tools in the data engineering sector.
We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination. Are you ready to embark on this exciting journey with us?
We make things happen
We act decisively and with purpose, going the extra mile.
We build
together
We foster relationships and develop creative solutions to address market challenges.
We are here to help
We are accessible and supportive to colleagues and clients with a friendly approach.
Our People Pledge
Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.
Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.
By applying, I confirm that I have read and accept the Staff Privacy Notice
Kpler
Analytics
Big Data
Finance
Image Recognition
Information Technology
Oil and Gas
Predictive Analytics
Software
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