Définition du poste / la mission générale du poste:

Responsible for providing analytical support related to user growth and content, performing market and competitive analyses. Identifying key market trends and telling stories with data. Passionate about finding insights in large datasets. Synthesizing and communicating results, and driving practical business impact. Work crossfunctionally with the product, IT, Strategy, MKT, Analytics & Finance teams.

Taches Principales :

• Conduct undirected research and frame openended business questions
• Extract huge volumes of data from multiple internal and external sources (sources DB, web, logs...)
• Employ sophisticated analytics programs, machine learning and statistical methods to prepare data for use in predictive and prescriptive modeling 
• Thoroughly clean and prune data to discard irrelevant information
• Explore and examine data from a variety of angles to determine hidden weaknesses, trends and/or opportunities
• Devise datadriven solutions to the most pressing challenges
• Invent new algorithms to solve problems and build new tools to automate work
• Communicate predictions and findings to management and IT departments through effective data visualizations and reports 
• Recommend costeffective changes to existing procedures and strategies
• Write and interpret complex SQL queries for standard as well as ad hoc data analysis purposes
• Being the goto person for any data question

Conditions d’Accès :

Diplômes & Formations : BAC+5/Master/ Ingéniorat / in Applied Math, Statistics and Computer Science (Bac+5);

Expérience : Minimum two (02) years of work experience involving quantitative data analysis to solve problems

Compétences :

Liées au métier :

• Math and Statistics skills 
• Machine learning tools and techniques (e.g. knearest neighbors, random forests, ensemble methods, etc.)
• Software engineering skills (e.g. distributed computing, algorithms and data structures)
• Data Warehouse and Data mining
• Data cleaning and mugging
• Data visualization and reporting techniques and tools (SAP, Qlik, Tableau, …)
• Unstructured data techniques
• R and/or SAS languages
• SQL databases and database querying languages
• Python (most common), C/C++ Java, Perl  Big data platforms (Hadoop, Hive & Pig, ...)