Which one is a better option: 1) MS in machine learning from University College London (UCL) with full funding (tuition/living/flights) or 2) MS in applied statistics & data science from Cornell with a $50K expense?

The most important thing you need to ask is where you want to work after college. That decides your question for the most part. If you plan to work in the US, it would make sense to go to Cornell. I'm not sure how many east coast companies recognize UCL. There might not be a lot of UCL alumni in NYC or Philadelphia. More importantly, visa restrictions and travel time would make it hard for you find a job in the US after you do your studies in UK.  In the same way, if you plan to work in London, you could consider going to UCL, as the same thing works in the opposite. Job search depends on networks, brand recognition and attending a lot of events/meetings. Geography matters for all these 3. Now, you need to figure out whether you can risk $50k. There is one answer to this. Some can and some can't. Some people figure they can make the $50k in 5-6 months of salaries, while others justifiably worry about ballooning loans during the period you are looking for a job. No one can make this decision for you, other than yourself. Your Visa restrictions are also important. Not being able to work in the UK after education would be a big bummer. You should ask yourself then what is the point of spending 2 years in the Masters there. It is not easy to shift to US, the H1bs are very hard to come and without a F1 OPT you will be in a very bad place. Finally, consider other choices besides these two. They look rock [overexpensive $50k education] and hard place [can't work after graduation] for me. See if you have a 3rd option.

Both are strong enough names and programs. You seem to be looking to advance your career, so I'd recommend a program that is more practically than theoretically focused, and the Cornell program sounds slightly better in that regard. $50K + expenses is not a trivial amount of debt however. You are probably foregoing 1-2x that in earnings too. So, it's a big but not huge differentiator. I think NYC and London are comparable job markets. Cornell is not in NYC, but UCL is in London. I know that post-study work is hard in the UK. Is it actually much easier in the US? this is probably the biggest difference, if you are sure you are looking to follow your study with work in one of these countries. I would recommend UCL except for this last factor. If you can't work here in the UK, and you can work in the US after Cornell, then I think I have to recommend Cornell.

Are you interested in working right after Masters or are you interested in a PhD? If PhD is the goal, go for UCL and then you can move to USA for PhD immediately.  As you have complete assistatship in UCL and will surely get into PhD with full aid later, this is a great option if R&D, teaching is your interest.  Even if you are considering PhD at a later point, pursue this. If Masters is the goal on the other hand, UCL primary curriculum is much more machine learning oriented.  If you are allowed to work in other European nations, you can consider it seriously.  Cornell program is quite statistical.  While elective options are there, it looks like you must go out of your way to take them.  But, work permit is a huge advantage.  Based on that alone, I recommend Cornell.  50K is not a major thing compared to 21 months of OTP.

Both programs should give you the fundamental knowledge necessary to move your analytics/Data Science career forward. My one big question is, if you have been working as a Data Scientist for the past 5 years, why do you want to go back to school to study Data Science? The answer to that question should be pretty telling. Aside from that, I'd say 2 things: 1) Where do you want to work? If you want to work in the UK, go to UCL. You can't be the free tuition + living expenses. And, you'll be really close to the job opportunities that you want. If you want to work in the US, then go to Cornell. Cornell is closer to NYC AND Cornell has much higher brand value in the US than UCL does. 2) Assuming that you're working as a data scientist now, you're looking at a minimum of a 6 figure opportunity cost to attend Cornell. So, before you decide you want to go there, make sure that the education will either propel your career forward enough to cover that opportunity cost, or that you will get a lot of personal fulfillment out of pursuing a graduate degree. Luckily for me, I got both out of my grad degree, but there was a real risk that I did not, and I wish someone had explained that to me before I made my decision. Best of luck!

There isn't a binary choice here. Your chart shows half the answer - you are choosing between the 13th and the 39th. If you can get accepted by these guys, why not go for the top ten? What you are buying is a badge. One which tells people that you are employable and will do a good enough job for them to be worth a big salary. But those badges aren't worth what they were. Because the University of Life these days also offers a badge - one which shows up at the top of your LinkedIn profile etc. People now judge you on the projects you've worked on, not just the bit of paper in your pocket. The other benefit of college is the people you meet. People who, through an old boys network, hand you work for the rest of your life. That's a 19th century idea and while it still exists, it hasn't the strength it once had. The unsaid question here is why you haven't built these contacts already. You've had five years as an Analyst/DataScientist. So you should have solid projects you can showcase. You should have solid contacts, not just in your existing jobs but through being part of Meetup Groups, Professional Bodies and from simply making connections online. If you have these, what is the degree for? You'll find you step back into the past on a degree course, because of the academic paradox. People like proof that an education is worthwhile, so Universities will always choose the guy with 20 years experience in a big company over the guy who is doing groundbreaking stuff now. The course materials are written by the same sort of people. So you end up being taught by people who are 20 years behind and probably weren't cutting edge in the first place (if they were that good at datascience, what are they doing in teaching?). These are people you, if you've been at the cutting edge in datascience for five years, you can buy and sell. The clever datascientists aren't in any University - they're out there pushing back the boundaries in companies. So it can't be for the knowledge. So is it for the badge? Universities would have you believe they're about getting the best from their own country and making them the best the country has. But the reality is that they've always prioritised money over talent. The sons of kings, barons and Lords, over the peasant with a powerful brain. But in the last half of the last century globalisation changed even that. They now specialise in taking the sons of the the privileged in emerging countries and giving them a British or a US education. Tinpot dictators like Idi Amin flaunted their Oxbridge education. These Universities are selling immigration by the back door. A badge which says that even though you are from the third world, you are first world standard (how colonial is that?). It may be that what passes for datascience in your country isn't world class and you need a badge saying "I'm World Class". That your experience in datascience is actually quite low level and you have recognised the boundaries of your learning. Let's not denigrate either of those - it happens. But they are different reasons for going than getting the best tuition or learning something new. So I would use my five years and all my contacts and get a job with a company doing something really interesting. Meanwhile I would do some courses - you can learn machine learning in 12 weeks, you don't need to waste 3 years of your life. I would build connections. Read papers, follow people doing clever stuff and get out there and meet top datascientists you can work with. And I would find my way into a project where I can really shine and put that on my CV, not a degree from an old, slow academic institution. Don't go backwards to go forwards. You're not in the 19th century anymore.

IMHO, You don't necessarily have to go for MS since you already have 5 years of experience in analytics and data science, although that also depends on what kind of experience you have. If you have made up your mind on MS , then go with Cornell. If your aim is to get a job in this field only, then  you can showcase your work, enhance your maths, stats and programming from open courses, sincerely solve Kaggle problems and you are good to go. If you want to get into the research side of ML (Machine Learning) and statistics then MS in a related field will help, PhD even better If you want to make a shift to business or managerial aspect of data science then may be an MBA might help.

If I was in your position, I would pick UCL (assuming, both the US and the UK are foreign land to you). If you belong to one of these countries, you should definitely consider home advantage. As they life is 20% of what happens to you, and 80% of how you respond to it, I can say, what matters more is how you perform rather than which college you went to (obviously to institutes should be comparable).

Cornell, Since you can work in US after studies. You can easily repay your debt within 1-2 years of your graduation.