  In this report, we propose a new application for twitter data called
\textit{job detection}. We identify people's job category based on their
tweets. As a preliminary work, we limited our task to identify only IT workers
from other job holders. We have used and compared both simple bag of words
model and a document representation based on Skip-gram model. Our results show
that the model based on Skip-gram, achieves a 76\% precision and 82\% recall.
