Let me first clarify that I am starting my journey into data science from a programmer and database developer standpoint. I am not a 10-year data science expert nor a statistical god. However, I do work data scientist and large datasets for a company that works with rather large clients worldwide.
From my experience, data scientist use whatever tools they need to get the job done. Excel, R, SAS, Python and more are all tools in a toolbox for good data scientist. The best can use a wide variety of tools to analyze and crunch data.
Therefore, if you find yourself comparing R to Python, then you're likely doing it all wrong in the data science world. Good data scientist use both when it makes sense to use one over the other. This also applies to Excel.
I think that it's rather hard to find anyone that is going to have experience in so many different tools and languages while been great at everything. I also think it's going to be hard to find data scientist specifically that can not only program complex algorithms but also know how to use them from a statistical standpoint too.
Most of the data scientist I've worked with come in about 2 flavors. Those that can program and those that can't. I rarely work with data scientist that can pull data in Python, manipulate it with something like Pandas, fit a model to the data in R and then present it to management at the end of the week.
I mean, I know they exist. I've read many data science blogs from guys developing web scrappers, pushing it into Hadoop, pulling it back out in Python, programming complex things and running it through R to boot. They exist. They're out there. I just haven't ran into too many that can do all of that. Maybe it's just my area though?
So, does that mean only specializing in one thing bad? No. Plenty of my friends specialize in just one main language and kill it. I know plenty of data guys who only know R and kill it. I also know plenty of people who just use Excel to analyze data because that's the only thing most non-data scientist can open and use (especially in B2B companies). The question you really need to answer is if this one thing is the ONE thing you need for this position? And most importantly, can they learn new things?
Data Science is not just restricted to "BIG DATA" or NoSQL.