As future data scientists and analysts, we believe that knowing the latest trends of data science job market is a key to employment. Our goal of this project is to have better insights on most in-demand technical skills and positions and the regions and types of companies that are in need of data scientists.We used a raw dataset of 1911 job descriptions extracted from CVs and turned it into a basetable with 1911 observations and 27 variables (for details,please refer to the Methodology and Results tab).98% of job descriptions are in English (1871 observations), but on very rare occasions, they are also in French. For pre-processing and text mining, we used the following packages and techniques: tm_map, stringr, openNLP, Regex, SnowballC, slam, RWeka, cld2, and Matrix.

James Ponce, Remo Boesiger and Deborah Kewon