Here I am talking about small countries with 10 million or less inhabitants, with good universities and high standard of living: places such as Switzerland, Singapore, Ireland, Belgium, Greece, Netherlands etc.

For data scientists, the challenges are as follows:

• Government has rather small data to analyze, compared with big countries. So governments data scientists do not work on big data, and might not be exposed to the latest technology.
• Big companies typically have their headquarters located elsewhere. So corporate data scientists do not have the chance to work on big, worldwide data. Even analyzing all the consumer data of a small country is small data science. This might not be easy to change, as the qualified workforce is found in places such as California and New York.
• There is sometimes a feeling of being somewhat inferior: when I studied in Belgium, my colleagues told me that we had no chances to successfully compete with Indian, Chinese, American or Russian scientists, as they outnumbered Belgians by a factor 10 at the minimum - and growing faster.
• The language is sometimes a barrier. In Belgium (South) a university professor must speak French. This considerably limits the pool of applicants, and thus the quality of education. In Switzerland, a recent law has been passed to make it almost impossible to recruit foreigners - hitting research very badly. In Quebec, they even forced me - a French native speaker - to rewrite one of my papers (when presenting at a conference in Montreal) using only French words authorized by the government ('digital' was deemed too American, I had to change it to 'numerique' - these dinosaurs believe that they can force a language on people, they don't know that languages are live, evolve with people, and can not be successfully regulated - but that's another story).

Solutions

At least, some people start to notice that a number of data science thought leaders are coming from small countries, and feel very encouraged by this. For instance, when 'small country' people learn that I also come from a small country, they get all excited and optimistic, and start doing things that they otherwise would not do, such as creating a very popular blog. We should also create an organization such as Small Country Data Science Society. Together we would be bigger.
In some countries (South part of Belgium where I come from), there is a very strong anti-entrepreneur spirit, and any new business is taxed heavily; doing business is considered evil (all entrepreneurs are leaving as soon as they can).

Changing this mentality might be impossible and a lost battle, but you have several options:

• Leave your country: easier to do after acquiring a certification such as our free, online DSA, or Coursera training
• Create (incorporate) your company abroad but stay in your country. I've been thinking creating companies in US on behalf of residents in other countries, in exchange for a 1% ownership or a fee. It's a risky business and I won't probably have the time to do it, but maybe solutions already exist.
• Work remotely for a company in another country. We have a guy in Eastern Europe working for us, and it's working very well for both of us.
• Set up a business that creates passive income, such as a website generating money from Google AdWords - you probably don't need any licence or authorization to start such a business in your country - it might not even be considered a business. Other examples: a website selling Amazon books (you get a commission from Amazon, on each sale), or selling data or whitepapers, and accepting credit card payments via Paypal.
• Work on Kaggle competitions - this might give you free access to big data, though revenue is probably unpredictable. But you can do it in combination with my other suggested options..

Other links

• How to detect spurious correlations, and how to find the real ones
• Data science job ads that do not attract candidates, versus those t...
• Data Science and Analytics Jobs
• Hadoop resources
• 17 short tutorials all data scientists should read (and practice)
• 10 types of data scientists
• 66 job interview questions for data scientists
• Our Wiley Book on Data Science
• Data Science Top Articles
• Our Data Science Weekly Newsletter
• Practical illustration of Map-Reduce (Hadoop-style), on real data
• What makes up data science?
• Data science webinars
• Data science competition