Qim info ? Qualité & Ingénierie & Méthodes !
Nous sommes une société de service en informatique de 230 collaborateurs, travaillant sur des missions IT dans des secteurs variés (banque, finance, industrie, administration, organisations internationales etc…) sur Genève, Lausanne et Grenoble.
Pourquoi nous rejoindre ? Proches, fidèles et pragmatiques, nous visons l’excellence, et la satisfaction de nos collaborateurs ainsi que de nos clients.
Notre expertise dans le domaine de l’IT est notre force, l’humain au cœur de nos valeurs.
Join our new Data Science Team !
R language, Hadoop, Spark, Machine Learning, Data segmentation, Artificial Intelligence, GBM, Big Data, TensorFlow, Jupyter Notebook… these are words that are part of your everyday life ? And you also love Python or another similar language ?
You will for sure find here an internship made for you !
You will :
Collaborate with the Data Science Team to get inspired and discuss about our client’s projects
Work closely with the project team to design, develop, test and deliver AI solutions
Develop strategies to extract, organize, manipulate and unify information of various types from disparate data sources
Work on data modeling (logical and physical), data architecture, data analytics technologies
Define algorithms and architectures to perform statistical data analysis
Exploit matching patterns leveraging AI and machine learning concepts
Report and organize workshops to help our clients to drive business decisions (technical and non-technical audiences)
Present AI POC to the business teams as well as the IT team in charge of the Data Science, including a part about the involved technologies and the way to industrialize the solution
Examples of concrete topics :
Calculation of expected arrival time of recovery services regarding to real time traffic data (Data mining, machine learning, customers experiences)
Creation of a roadmap to identify most common sport disciplines through Switzerland according to data collected from sport magazines, stores and organizations (Data mining, machine learning, API development, sport, society behaviour)
Set a strategic time to launch a new product based on the analysis of target consumer’s consumption habits (Deep learning, marketing strategies)