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Data Science
vor 3 Monaten
Pays
Suisse
Lieu de travail
GENEVE-WTC1(CHE)
Société employeur
TOTSA TotalEnergies Trading SA
Domaine
Systèmes d'Information
Lieu
Switzerland
Expérience
Moins de 3 ans
- You are enrolled in a master's degree in computer science/data science
- You have skills in data processing and statistical analysis
- You have knowledge of basic machine learning and artificial intelligence concepts
- You have very good development skills, particularly with Python
- You have very good skills on Docker, Kubernetes ;
- You already work with Github or Azure DevOps ;
- English is essential
- You have a high degree of autonomy
- You are dynamic, methodical, rigorous and curious
- You are an educator and gifted in communication
- You are willing with a strong team spirit
- Knowledge of the maritime domain is a plus but not mandatory
Internship agreement is a mandatory
- At TotalEnergies, we believe that our employees' fulfilment has its roots in the wealth of the experiences they are offered. We are an equal opportunity employer committed to respecting diversity and inclusion in the workplace.
Activités
Are you looking to grow your career in the vibrant world of energies trading?
You have a solid experience in Data Science / Machine Learning? If yes, we have a great opportunity for you
**About us: TotalEnergies has developed a strong expertise in oil and biofuels, natural gas and electricity trading. Trading entities are based in Geneva, Paris, Houston and Singapore.
Today, thanks to an international openness, a political and economic stability and strong competences in the financing of commodity trading and shipping, Switzerland has a leading position in international commodity trade.
This is why TotalEnergies installed naturally its European trading hub across oil and biofuels, natural gas and electricity in Geneva, which now bring together very large teams around trading activities:**Trading & Shipping (T&S) and TotalEnergies Gas and Power (TGP).
T&S is a trading company in charge of all physical trading and shipping of crude oil and refined products on behalf of the TotalEnergies Company. It has been an active participant all over the supply chain as well as on the derivatives paper market in order to manage the market risk for a long time.
**Our Culture: We are committed to meet the energy needs of a growing population and we are committed to the energy transition. The volatility of the energy trading markets requires excellence in risk management and a culture of innovation. We are fully embracing the digital revolution.
Our people flourish in an environment that promotes expertise, entrepreneurship spirit, agility and a purpose-driven culture, generating boundless opportunities to learn, grow and achieve collaborative success.
Reinforcing the competencies of our people is a key pillar of our culture: we train our people to ensure their development and we pledge to encourage safety in all our actions.
We look for passion, ambition and open-mindedness.While we evolve in a demanding industry that requests to be always on the edge, we cultivate a friendly workplace where our people feel good, where team spirit and respect guide our daily routine, where the diversity of our people and their skills create a nourishing experience for all of us.
What you will do
- Build a documented and reliable referential of ports, berths and zones.
- Conduct an indepth analysis of the current state of the art in maritime distance calculation.
- Design and train machine learning models to estimate distances between ships, coastlines, or other maritime objects.
- Collaborate with our development team to industrialize these models via ML Ops processes.
- Test and validate the performance of the maritime distance calculator using realworld data.
- Contribute to model optimization to improve accuracy and reliability.
- Document the development process, models, and achieved results.
Contexte et environnement
**Job dimension
As part of the Trading's Data Science and Analytics team, you will work closely with our Shipping Market Analysis team.
Your main mission will be to design, develop, and implement a maritime distance calculation system using machine learning techniques.Calculating the shortest maritime route between two geographical locations can present a complex challenge.
Current solutions, like the open-source algorithm 'searoute,' use Dijkstra's algorithm to find the shortest path but the process can be slow and only provides an approximate solution due to the issue of node interpolation.
For this internship, we're seeking an aspiring data scientist to leverage machine learning algorithms to improve upon