Internship / Stage Bac+4 - Quant - Neural Network
Il y a 4 mois
Murex is a global fintech leader in trading, risk management and processing solutions for capital markets.
Operating from our 19 offices, 3 000 Murexians from over 60 different nationalities ensure the development, implementation and support of our platform which is used by banks, asset managers, corporations and utilities, across the world.
Join Murex and work on the challenges of an industry at the forefront of innovation and thrive in a people-centric environment.
You'll be part of one global team where you can learn fast and stay true to yourself.
**Équipe**:
L'équipe «MACS» est responsable de l'implémentation des méthodes d'évaluation innovantes et efficientes cross-assets (Action, Change, Matières Premières, Crédit et Taux). Cela comprendd'une part la compréhension des modèles standards et la conception éventuelle de nouvelles modélisations adaptées aux besoins du marché et d'autre part l'implémentation et la maintenance de solutions (librairie quantitative, service...) permettant la calibration des modèles et l'évaluation et le calcul des mesures de risque (sensibilités, VaR, PFE, XVA...) des différents produits financiers. Une attention toute particulière est portée sur la précision des différentes méthodes implémentées ainsi que sur l'optimisation des temps de calcul, ce qui nécessite d'adapter les solutions aux technologies les plus innovantes (GPU par exemple).
**Missions**:
En finance, la capacité à évaluer rapidement et précisément le prix de produits dérivé s est essentielle pour la prise de décision et la gestion des risques. L'utilisation de réseaux de neurones, avec un apprentissage supervisé, offre un gain de vitesse important par rapport aux méthodes numériques traditionnelles (Monte-Carlo, EDP ), tout en réduisant les coûts matériels grâce à une utilisation plus efficace des ressources informatiques.
Ce stage vise à approfondir la mécanique d' entraînement des réseaux de neurones dans ce contexte. Il se concentrera sur plusieurs hyperparamètres clés de l'optimisation : le choix de l'optimiseur, le taux d'apprentissage, l'initialisation, et la taille de batch. L 'objectif est de déterminer les meilleures heuristiques afin d'améliorer l a précision d e nos réseaux de neurones. D'autres hyperparamètres pourront être étudiés par la suite.
**Profil**:
- Étudiant en seconde année d'École d'Ingénieurs/Informatique.
- Vous avez de bonnes connaissances en Python (des connaissances en C++ sont un plus).
- Vous êtes intéressé par le «Deep Learning».
- Vous êtes intéressé par les marchés de capitaux et la modélisation d'actif financier.
- Dynamique, rigoureux, et autonome, vous êtes capable de travailler dans un environnement agile.
- Bonne communication orale et écrite en français et en anglais.
**Pourquoi nous rejoindre ?**
- En intégrant l'équipe MACS (Murex AnalytiCS ), vous travaillerez sur un sujet stimulant et innovant.
- Vous évoluerez dans une équipe motivée et engagée cross-assets et cross-technologie
- Vous aurez à disposition si besoin les dernières technologies (GPU par exemple).
- Vous évoluerez dans un environnement agile, international, multiculturel et en croissance.
**Durée**: 3 mois
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