Qui sommes-nous ?
Data Scientist Intern
- Type de contrat : 620e7be75b0a7
- Type de contrat : Stage long (6 mois)
- Niveau d'études : Bac + 4
- Expérience requise : Moins d'1 an
- Salaire : non précisé
- Lieu de travail : non précisé
Mission
Fonctions et responsabilités :
- Categorize transactions of the users to help them keep track of their budget
- Build specific fraud detection algorithms to enhance the global fraud detection framework
- Search for new features describing users to enhance the credit scoring models
- You will work on cool technologies on GCP (Python, Tensorflow, Jupyter, Docker, ElasticSearch, Redis, MySQL, RShiny)
- You could work on NLP or vision stacks
Profil recherché
- You are preparing a MS in applied mathematics/computer science from an engineering school or university
- You know a little bit of SQL and Python
- You are curious, autonomous and like to dig into the data to find powerful insights in your models
Informations complémentaires
With over 5 million active users and an impressive 5,000 new customers joining every day, Lydia aims to become one of Europe’s leading financial services organisations. Founded in 2013, Lydia has been recognised as one of France’s most promising start-ups through its recent inclusion into the "Next 40" ranking.
After raising €112 million from investors in 2020, we have plans to accelerate our European deployment while continuing to offer additional innovative solutions. From top-security contactless mobile payment to a wide array of app-based services, Lydia puts people at the centre of the digital banking experience
Part of our growth strategy is centred around attracting top talent to help us nurture our ongoing success. We are now looking for our new Data Scientist Intern.
Reporting to our Head of Data, you will join the Data team.
As part of the data-team, you will collaborate with Lydia’s data scientists on different topics to improve the features describing users, transactions and products. You will also research, develop and test new methodologies to tackle our technical challenges regarding fraud detection, credit scoring, marketing targeting and personal finance management.
Mission
Fonctions et responsabilités :
- Categorize transactions of the users to help them keep track of their budget
- Build specific fraud detection algorithms to enhance the global fraud detection framework
- Search for new features describing users to enhance the credit scoring models
- You will work on cool technologies on GCP (Python, Tensorflow, Jupyter, Docker, ElasticSearch, Redis, MySQL, RShiny)
- You could work on NLP or vision stacks
Profil recherché
- You are preparing a MS in applied mathematics/computer science from an engineering school or university
- You know a little bit of SQL and Python
- You are curious, autonomous and like to dig into the data to find powerful insights in your models
Informations complémentaires
With over 5 million active users and an impressive 5,000 new customers joining every day, Lydia aims to become one of Europe’s leading financial services organisations. Founded in 2013, Lydia has been recognised as one of France’s most promising start-ups through its recent inclusion into the "Next 40" ranking.
After raising €112 million from investors in 2020, we have plans to accelerate our European deployment while continuing to offer additional innovative solutions. From top-security contactless mobile payment to a wide array of app-based services, Lydia puts people at the centre of the digital banking experience
Part of our growth strategy is centred around attracting top talent to help us nurture our ongoing success. We are now looking for our new Data Scientist Intern.
Reporting to our Head of Data, you will join the Data team.
As part of the data-team, you will collaborate with Lydia’s data scientists on different topics to improve the features describing users, transactions and products. You will also research, develop and test new methodologies to tackle our technical challenges regarding fraud detection, credit scoring, marketing targeting and personal finance management.