[Arsonism]

I'm not sure what to expect from this thread, but I figure it's best to reach out than to just keep wandering the internet to just reach random data about things people may or may not be doing with such backgrounds or careers; so here we are.

I have my Bachelors currently and I'm considering pursuing a degree in Statistics in order to yield (what I've obtained so far) a data specialist or consultant role for companies in the future. I have worked more or less as a Data Analyst (entry work, SQL/Excel programming/database creation, etc) and during audit periods as a Compliance Manager for a company operating in the oil and gas sector, and as far as I'm concerned it was my most favorite period of work that I've been assigned (outside of military work - I get to do some pretty cool stuff there).

My question's are mainly about the field after someone might consider a masters level degree in Statistics, and if anyone can speak to either the consultation that they have received from a statistician or their experience as performing the duties of one. This is to ultimately help me assess the value of this degree.

Some subjects I'm still curious about are:

What are the roles that someone with an MS in Statistics is typically found in?
What sort of programs do they use (SPSS, SP+, Matlab, etc)? Do they commonly write code?
What upward progression is there for a data analyst?
What progression is there for "Big Data Scientists?
What would you say appear to be or are the best features of this line of work?
Does consultation generally win out in terms of income over working solely for one company or organization?

I'm sure I'll find a slew of other questions to ask, but I think that would cover most of it for now. Just like any job, I'm just curious to know what it's all about and what I'd be getting myself into. I've leaped into career paths before and it's bit me in the butt, doing my best to make an educated decision on the remaining opportunities I have to chase down another degree.

I sincerely appreciate y'all's time.

Thanks,

Shane