Data Engineering

The production of new and unstructured Big Data (voice, text, image), the advent of open data, and the ever-evolving capability to stock and treat data have open up new fields for data engineering. Big Data experts with mastery of both Computer Science and Statistics have become highly sought after. 

A Data Scientist who has studied the “Advanced Tools for Data Science and Machine Learning” program at ENSAI has in-depth knowledge of Computer Science as well as expert knowledge in Statistics. As an expert in Big Data, s/he has more than adequate knowledge in Systems Architecture, Networks, and IT Security to handle large volumes of data, create data storage solutions, and conduct multidimensional analyses on data. S/he also masters web semantic technologies.

Multi-Sector Relevance

The three major sectors for applying Big Data are industry (16.4 billion euros invested in 2020 in the EU), finance (15.4 billion euros), and retail (8.2 billion euros)*. Beyond these fields, Big Data impacts numerous data-driven projects in the energy, transportation, health, and media sectors. These non-specialized experts can therefore put their skills to use for the whole economy. 

Big Data and AI

The Data Science & Data Engineering specialization opens up numerous opportunities to pursue a PhD with numerous research topics in Data Science involving Machine Learning and Deep Learning linked to Artificial Intelligence. AI algorithms have begun to reach a level of technological maturity which is expanding on the promises made by Big Data at the end of the 2000s. The impacts and applications of these advances are at the heart of the challenge facing Data Scientists today.


Software Engineering /Digital Analysis / Statistical Machine Learning / Deep Learning /AI


Data Scientist / Social Network Analyst / Risk Manager /  Big Data Health Analyst / Supply Chain Optimizer

Businesses within the ENSAI ecosystem

Capgemini / EY / Lincoln / Naver Labs / Orange / Solocal Group / Safran / Thales / Ubisoft…

Course catalog