Internship Refineries Optimization and Modeling @ Kpler in Paris, Athens, Rostock, London

​​At Kpler, we simplify global trade information and provide valuable insights. Founded in 2014, our goal is to help over 10,000 organisations by offering the best intelligence on commodities, energy, and maritime through a single platform.
Working at Kpler means you’ll be a key player in turning complex data into strategic resources for our clients. Your role involves creating data-driven stories that empower clients in their industries.
Your expertise helps Kpler navigate markets successfully. Your journey starts here, where innovation meets impact. Join our team of 500+ talented people from 35+ countries worldwide.
The team
The refineries team is building a state-of-the-art product that aims to provide insight into crude oil consumption, refined product production, and gross margins on a daily basis. The team is aggregating and combining a wide range of datasets using advanced Operations Research (OR) techniques. As a new product in the Kpler portfolio, we have high ambitions and want to build a great product to help people make more informed decisions.
Your objective
To reliably publish accurate data on a timely basis, the team faces different categories of challenges, from difficult modeling problems to scalability concerns. As a trainee, you will join the team to enrich our LP model by combining submodels and enabling them to leverage data that wouldn’t otherwise fit in. You will be required to run R&D work by looking at the bibliography, running experiments, picking the right solution based on product requirements, and then integrating it into our production pipelines following software engineering best practices.

More specifically, you will be asked to:

    • Model new constraints to simulate the dynamic aspect of the refineries’ production plan regarding the market conditions. 
    • Use transformation and linearization techniques to simplify some complex constraints.
    • Use approximation and decomposition techniques to solve larger models at the country or region level that involve solving the model of multiple refineries at once.

Your skills and experience

    • You are currently attending a postgraduate (M2) degree in computer science, applied mathematics
    • Strong background in linear programming and mixed-integer programming
    • Good knowledge of linearization, approximation, and decomposition techniques
    • You have practical experience using an LP modelization toolbox (Google ORtools, Cplex, Gurobi)
    • You have practical knowledge of Python and SQL
    • You are willing to learn about the commodity/energy world
    • You understand software industry best practices and are ready to observe them
    • You fluently speak English
We’re a dynamic company dedicated to nurturing connections and innovating solutions that tackle market challenges head-on. If you’re driven by customer satisfaction and thrive on turning ideas into reality, then you’ve found your ideal destination. Are you prepared to embark on this exciting journey with us?
we make things happen
We act decisively and with purpose, and we like to go the extra mile.
we build
together
We foster relationships and develop creative solutions to address market challenges with cool features and solutions.
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Being accessible and supportive to colleagues and clients with a friendly approach is essential.
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.
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