The future is bright, BUT you have to get into the right position. Data
scientist is hot although the actual responsiblities vary a lot. You may end
up with doing some data cleanup and playing around to extract useful
features.
There are serveral pillars for big data paradigm: Cloud or say large
distributed processing infastructure, machine learning, visulization, etc.
Infastructure wise, hadoop(map-reduce) is a famous one. There are also lots
of works on real-time event processing, in memory DB and column based DB.
Lots of innovations happen in Paralell RDMS as well.
ML: Get a book to understand classifier, decision tree, SVM. If you know how
to use them, that's good enough. Deep learning is super hot, so you can
take a look. NLP is a plus in many JD.
Visulization: That's a big part. Many many startups working on this.
It's a complicated task to build big data pipeline in different companies.
The demand is very high and kept growing.If you have a strong combinations
of aforementioned areas, you are chased by recuiters. The pay should be
decent and you have more chance to get into star startups.
Without strong background, it's very hard to get a data scientist position.
