Higher education (engineering school or university), ideally supplemented by a course in an English-speaking country
First successful experience in a consulting firm or large company in analytics or data science disciplines
Participation or management of large-scale projects in data management, analysis, and interpretation
Dynamic and enterprising personality
Competencies in one or more of the following: Databases (SQL Server for Windows, PostGreSQL, MySQL, MongoDB); ETL (SSIS, Talend, Informatica); Big Data (Hadoop, Spark, Hive, Hortonworks HDP, Cloudera); Programming (SQL, SAS, R, SPSS, Python, C#, Java); Statistics; Machine learning; Visualization (QlikView, QlikSense, Tableau, PowerBI, D3.js); Data virtualization
Responsibilities
Data analytics and data mining in operational and financial diagnostics across all activity sectors
Audit and control analytics: implementation of advanced data analysis techniques to replace traditional audit procedures
Predictions and modeling on regulatory or financial business topics (e.g., quantification, credit risks), as well as operational missions (e.g., sales forecasting, project risk forecasting)
Data visualization: implementation of dashboards and exploratory analysis tools on client risk data
Design of technological solutions adapted to client needs and missions from a "data" perspective: structuring, architecture, modeling, analysis engine, integration, user experience