I have an M.S. in statistics, am a good R/SAS/SQL programmer, I have taken the coursera ML course, and am currently working as principal statistician for an energy company. What else should I do to become qualified for 'Data Scientist' positions?

Any specific languages I should learn, books to read? Anything is appreciated. I already do tons of ML at my job daily (most statisticians don't think of it as ML stuff though), but can't help feel there is something I am missing that would qualify me as data scientist.

I should mention, I am also pretty good at Octave/Matlab and am ok at Python (would be better but I never get a chance to use it). My masters thesis was on non-Gaussian time series and multivariate predictive methods, I also took a few courses in Bayesian econometrics/analysis.

edit: Thanks a ton for the advice so far, the consensus seems to be start learning how to deal with big data using Hadoop or some other similar app and learn some software engineering, however that part seems a little ambiguous still.