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How to start applying for Analytics / Data Science Masters in the US Universities?

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Planning a masters program in data science in US? But, not completely aware of the application process? Or afraid of the application process? Don’t worry. I’m here to help. I will take you through the complete process required to apply for analytics / data science programs in the US. Also, I’ll share some useful tips to help you get over this process faster.

You must be thinking, how do I know this process ?

Because I have gone through the entire process myself. I am going to pursue MS in Data Science at Columbia University in Fall 2016. Though, I also had admits for MS in Analytics at Georgia Institute of Technology and MS in Analytics at Northwestern University. Not heard of their names before? Well, you must check out my previous article.


Table of Contents

I have divided the complete application process into 4 phases, precisely as follows:

  1. Mental Preparation
    • Start looking at programs in US Universities
  2. Taking Pre-requisite Examinations
    • GRE
    • TOEFL
    • Preparing for GRE & TOEFL
    • How much does GRE & TOEFL score matter in the application?
  3. Preparing and Submitting Applications
    • Finalizing Universities (where to go!)
    • Statement of Purpose (SOP)
    • A Good Strategy to Follow
    • Some more advice
    • Resume / Curriculum Vitae
    • Letter of Recommendation
    • Transcripts and Other Formalities
  4. Selecting from Admits & Flying to US

A couple of things to note before we proceed:

  1. Though the steps for MS applications are same for all engineering programs as well, but this article is particularly tailored for data science and analytics. Thus, same ideology might not apply elsewhere.
  2. There is some sort of chronological ordering in the steps which are highly recursive in groups, i.e. they’re not necessarily one after the other but few have to be done together at a particular. I will provide a timeline at the end giving a sample plan of how the entire process can be approached.
Statue of Liberty and New York City

Statue of Liberty and New York City



Phase 1. Mental Preparation

This is one of the most important step. The entire process is quite cumbersome and requires great endurance & patience which is difficult to find until you are determined enough to get into a masters program. You have to give it a good thought. Not only you, but your family also has to agree to this decision (if it matters).

In particular, you and your family should be mentally prepared for the following:

  • Financial Expenses:
    • Both the application process as well as the program are expensive.
    • The application process involved in preparing and appearing for GRE and TOEFL exams is costly. Each exam costs ~$200 and if you join any training institute, that fee is separate. Even sending the scores to universities is charged separately.
    • Even applying to each university costs ~$100 per university.
    • If you take help from any third-party in preparation of your application material, it’ll further add to the cost.
    • After getting an admission, you have to pay for the VISA, send transcripts, buy air ticket, etc.
    • Total expenditure before stepping into US would range between INR 2-3 lacs ($3000 – $4500).
    • Since scholarships are rare to achieve, if not non-existent, for data science and analytics programs, you should not expect any financial aid from university. So, the cost of program and living would depend on the university and location.
  • Time Devotion:
    • The entire process from appearing in GRE & TOEFL exams to applying for VISA, easily takes ~1 yr, if not more.
    • Most people (applicants) happens to be working or studying alongside so taking out time can become a challenge.
  • Staying Away from Family (if it matters)
    • This might not be a concern for all, but definitely for a good proportion of aspirants (It was for me :D)
    • The MS program would take 1-1.5 yrs. There are many 1 yr programs in analytics and you can opt for them but the good ones are mostly 1.5 years.
    • Most of us would like to pay our loans and thus average ROI period is ~2yrs, given you work in the US.
    • So you’ve to prepared for at least 3-4 yrs stay in US.
    • Regarding long term plans, data science is growing in India and you can get opportunities here after you work there for a couple years. They might not pay as well as US, but again its a trade-off to be made which depends on the individual.


Start looking at Programs in US Universities

Once you are prepared, you should get an idea of what exactly those programs offer. You should not go ahead with any wrong expectations. You should carefully analyze your profile, look at prospective colleges, the kind of people who get in there etc. In fact, you can also talk to people who have been through the process and ask them where would your profile fit. You can read my previous article.

This will give you an idea of what you’re getting into. You’ll also get to know a benchmark of the GRE score required for your desired institution. All this will help you plan your approach.

For instance in my case, I am a graduate from NSIT, Delhi University in Manufacturing and Automation Engg. So, I understood early that its difficult for me to get in right after college. Therefore, I worked in analytics and data science for almost 1.5 yrs before applying again.

I had targeted 320 for GRE and got 323 which is decent given my profile. I also had a chat sessions with many seniors, friends already in US and some professional consultants as well. Remember, that some things come only with experience and there is a limit to which Google can help in some situations.

There might be other constraints specific to your case. You should consider all of them and proceed only if you are mentally prepared. Get a feel of the programs and the future prospects of places you are more likely to fit in. Once you set yourself to this path, there should be no turning back!


Phase 2: Taking Pre-requisite Examinations

Now that you have taken a decision, the next step is to take the GRE and TOEFL exam and get a good score. It is important to get this in your head before you begin your application because:

  1. The scores will help you in selecting right universities.
  2. The score is required to be entered in applications.
  3. You should keep sufficient time for a re-attempt, i.e. in case you get a bad score, you should keep a month atleast to prepare further and try again.

Lets try to understand each of these exams separately.

GRE (Graduate Record Examination)

The GRE exam is designed to test your aptitude. It assess your logical reasoning and grasp over english language with quantitative ability and verbal ability sections.

The exam contains 6 sections – 3 verbal and 3 quantitative out of which 1 is not graded, but we don’t know which one that is. Also, it is a section-wise adaptive exam, i.e. the difficulty of the next section depends on the score of the previous. So, if you ace your first quantitative section, the next one will be difficult and vice-versa.

  • Quantitative Ability
    • This section contains simple mathematics which we generally study till 10th standard in CBSE board (in India).
    • Majority of questions will be easy. The only trick is to keep an eye for detail and not take it for granted.
    • Scoring a 160+ is a cakewalk, 165 is slightly challenging but every mark above it is worth achieving. That’s not because the questions are hard, its just that it is hard to maintain focus on such a long test. Getting a 170 is definitely possible if you’re at your best.
    • Remember that the test is adaptive and there are high chances of you acing the first section. This would result in a relatively difficult second section with 1-2 hard questions.
    • I can’t over-emphasize the fact that its all a matter of focus and some practice. Just treat it like an exam and you’ll do well. I’ve seen people highly underestimating quant and ending up in 160-165 range. I practiced a lot which helped me to score 169!
  • Verbal Ability
    • This is going to be the difficult part for most of us for whom English is a non-native language.
    • Once you start preparing, you can expect all sorts of words which you never came across in your life. Vocabulary plays a crucial role and there are a good 1000-1500 words which you should have a sense about.
    • Along with vocabulary, the reading comprehensions are also challenging as they really require a deep understanding of the context. In many cases, almost all of the answer choices are very similar with subtle differences. Good amount of practice is required to ace these.
    • You should aim for something around 155 at least and take it forward from there is possible.
  • What’s a good score?
    • Overall 320 is considered a benchmark score which should get you in safe places. But there’s nothing carved in a stone. I’ve seen people with 315 cracking big universities and ones with 325 not able to make a mark. In the end, your profile would play a bigger role than GRE.
    • You should note that for programs like data science, mathematics will be given an emphasis for sure. So having a score of 320 with 160 each is not as good as maybe something ~170 in Quant and ~150 in verbal. But again it depends on the perception of each institute.
  • Analytical Ability
    • This is a third section of GRE which is graded out of 6. You’ve to write a couple of essays. First is, on any topic where you want to share your views. Second is, analysis of an argument where a passage will be given and you’ve to identify the flaws in the argument made there.
    • Personally for me, the former kind is difficult but even the latter isn’t a piece of cake.
    • If your writing skills are not good, you’ll need significant practice for this section as well. In my case, I had to work a lot on the first type of essays.
    • 4 (out of 6) is considered to be a good score here but even 3.5 works. Anything below that is not good. This is because if you’re having a low score here and you end up writing an excellent SOP (Statement of Purpose) then it raises concerns that the SOP was written by someone else.

The score of a GRE exam is valid for 5 years. In terms of preparation time, it would largely depend on your grasp over English. If you’re really good, you can do it in 3-4 months. I was average and it took me ~6 months. If you’re not even average, expect 6-8 months. Moreover, I believe that there is a level to which you can increase your score. After that the effort required is exponential and you might not get that much returns. So you’ve to identify that level for you and achieve it. Like I figured I was a 320 guy. So I settled for a 323.


TOEFL (Test Of English as a Foreign Language)

TOEFL is designed to test your grasp over English. It has 4 sections – Reading, Listening, Speaking and Writing, each with 30 marks totaling to 120.

Each section has questions in a specific format which you can find in any of the preparation books. I will not go into the details here. It is a relatively easier exam as compared to a GRE. Most of the questions will be straight forward and the scoring is also relaxed. There is another exam called IELTS which works more in the UK but some of the American universities also accept its score.

In terms of a good score, 100/120 is considered a benchmark. I would say that its fairly easy to score a 100. With some good practise, you can easily cross 110. I attempted the exam twice because it is valid for only 2 years. I scored 114 in first attempt and 117 in second and I studied literally for 3 days in my second time. So, you can imagine how easy the exam is.


GRE and TOEFL Preparation

Now comes the important question, how to prepare?

For GRE, I would recommend taking some sort of classes, either online or in-person. I personally took in-person classes at Princeton Review for GRE and I got a package with TOEFL exam included for around 4K. I really liked Princeton Review and I would definitely not have been able to get a 323 without there help.

I think most of us would need external help unless off-course someone is really good in English. It’ll really help if you like reading novels and newspaper. You should read some reviews about the center before joining because there are bad ones as well which will waste your time and money.

If you’ve decided that you are serious about it, I recommend you should start by learning new words. You can pick up the famous book Word Power Made Easy, Norman Lewis.

This is a really good book to start enriching your vocabulary. It uses etymology, which is a technique of learning words through there roots or origins. It has some interesting exercises to help you set a strong vocabulary base. Along with this you should start looking at some coaching centers in your area and once you feel comfortable with this, you should start the coaching as well. Reading this book as a primer will be really helpful.

Another word of caution – DON’T IGNORE MATHS! I know that quantitative is really easy and scoring even 165 is not very difficult. But in order to get a full score, you must practice sufficiently. I’ve seen many people who underestimate quant and end up scoring in the early 160s. Just take this part as an exam and it should be fine.

For TOEFL preparation, you can either buy a book and do it yourself, take an online course or just a package with your GRE coaching. Its not that difficult and should work out. Focus on getting the GRE done first and then go for TOEFL.


How much does the GRE and TOEFL score matter in the application?

This is a crucial question, one that many people wonder and generally over-estimate.

In my opinion, GRE would matter 2-10% depending on the university, generally being on the lower side. Trust me many people have asked me “How much GRE score is needed to get into XYZ university?” Honestly, GRE score is not the deciding factor. If you consider that different applicants are a part of a race, then GRE score would decide where you start. An approximate analysis can be done as follow (for universities for which 320 is considered a par score):

  • <300: lag of ~50%
  • 300-310: lag of ~20%
  • 310-315: lag of 10%
  • 315-325: almost around the starting line
  • 325-330: ahead by 5%
  • 330-335: ahead by ~10%
  • 335+: ahead by ~20%

I hope this analogy makes sense. The idea is to tell you that GRE score is important but your profile matters more. So you should decide the time you spend on getting a good GRE score wisely because that time can also be used to improve your profile.


Phase 3: Preparing and Submitting Applications

This is the most critical phase of the application process. It involves the following:

  1. Finalizing Universities
  2. Writing Statement of Purpose
  3. Writing Resume/CV
  4. Arranging Letter of Recommendations
  5. Arranging Transcripts
  6. Fulfilling university specific requirements

Lets consider each of these individually.


Finalizing Universities

This is the first step after you have scored GRE and TOEFL exams. You should select somewhere between 5-15 universities to apply to. Though, there are not many good universities offering programs in analytics/data science, buy you can still have a big list. My previous article will help you to refine your search.

The hard part is to decide which universities are safe for you and which ones are hard to get into. Honestly, its a very hard question to get an answer. Some of the tips you can use:

  • Look at class profiles of the programs. This will give an idea of the background of people who got into each program. If class profiles are not directly available, you can check with the program administrator or use social media, LinkedIn can really help here.
  • Talk to your friends/seniors who are already in US. Those guys would have done the research already and can give you some really good information.
  • Take help of career consultants. Mind you that they can charge you a hefty sum! Though, they can give you some ideas for sure, I’m not a big fan of consultants and I’ll cover this in detail later.

Finalizing universities is important because it will help you plan your applications based on the deadlines. Each university will have some common and some individual aspects. Thus, prioritization as per the deadline is really important for you to finish everything on time.


Statement of Purpose (SOP)

SOP is the most dynamic and open ended part of your application where you can speak your heart out.

Its importance cannot be over-emphasized and thus its pivotal to understand what a SOP actually mean. In my opinion, it is simply a reflection of your life. As the name suggests, it should endorse your fitness for the program.

The reader should feel that this program is tailor made for you and you were born to take the course. Its like a marriage, the higher the compatibility between the two (you and program), higher the chances of success. 😀

Some important points to take care while writing the SOP:

  • Support your statement with anecdotes
    • Don’t simply brag about yourself. If you’re saying you possess a skill, you’ve to justify how.
    • For example, a poor statement would be “I am an expert in machine learning. I can make various models for solving classification and regression problems on big data using a wide variety of ML models like regression, decision trees, random forest, GBM, etc.
      • It sounds fancy but if you observe closely, it looks like you’ve copied the names of some algorithms and reader is unclear about the extend to which you have used them.
    • Instead a better approach would be “I have gained substantial experience on ML algorithms through various experiences of my life. During my undergrad, I did a project on ….(details)… where I implemented a random forest model for classification. While I was working for XYZ company, I implemented a ridge regression model for solving ….(details of problem)…”
      • Here I’ve used just 2 key words – random forest and ridge regression as compared to the previous one.
      • It’ll still have a better impact because the reader now knows the situations in which I have applied the models which will help him gauge my skills.
  • Be specific and provide details
    • When you’re giving examples, mention as many details as you think are required for you to gauge someone else on the same matter.
    • For instance, there can be 2 types of details while mentioning an ML project:
      1. During my undergrad, I implemented random forest model for predicting the customer satisfaction of a bank’s customers.
      2. During my undergrad, I implemented random forest model for predicting the customer satisfaction of a bank’s customers using their financial, demographic and behavioural data. There were 100K data points for 35 variables. The model achieved an accuracy of 96.5% where the baseline accuracy was just 80%.
    • Which one do you think is better? #2 obviously. The key takeaway here is that you should mentioned as much details as required to define the activity properly.
  • The overall story should make sense
    • The information flow in your SOP should be coherent. When someone reads it quickly in say 1 minute, then it should leave a positive impact.
    • It should clearly portray 2 key pints:
      • How your past experiences prepare you to take this program?
      • How your future goals align with the learning you will get during the program?
    • You should have a good “story”, i.e. flow of ideas. Each paragraph should send a message. A good way to check is to write down the key idea of each paragraph in 1 line one after the other. Then read them together and they should make sense. Otherwise, a restructuring might be required.
    • Note that the story need not be chronological always. You can focus with your good points first and then go into your history but it should be done smartly.
  • The opening paragraph has to be a killer
    • The ideology of first impression works well in case of SOP. Your first paragraph is a very important part of your SOP. More than anything, it sets the mood with which the reader reads the remaining part of the SOP.
    • If its blunt and boring like the 100 other SOPs the person reads everyday, he won’t take much interest.
    • But if it is unique and if you’re able to sell yourself, then the reader will take interest in your SOP and read it with a positive intent.
    • The aim of the first paragraph is to justify the marriage proposal between you and the program. It should give an impression that you two are made for each other!
    • I’ve seen people using quotations, examples of prominent personalities like Einstein, Newton, etc. Use whatever you want. After all, everything is fair in love and war! Right ?
  • Show that you know the program well
    • How can you justify a marriage without knowing your other half? SOP works on a similar principle.
    • Not only, your experiences should implicitly justify the requirements for the program, but you also have to mention explicitly what you like the most about it.
    • Some people mention about the courses they like, others may mention professors doing specific research. You may like a particular society, the interdisciplinary nature of the course or any other special feature.
    • You just need to explore the program website and come up with interesting insights about the program.
  • Answer why that particular university
    • The same program is offered in many universities. So its important to write why you’re opting the particular college.
    • It can be in just 1-2 lines but it definitely should be there.
  • Stay away from information overload
    • Even if the university doesn’t set any page or word limits, your SOP should be within 2 pages.
    • If you think you’ve done too much work to be justified in 2 pages, then you’re most probably wrong. It simply means that your quality of writing is not good enough to present your work in less words.
    • Keep reviewing and revisiting your SOP. Get it peer reviewed. Crunch every extra word out. Just keep it within 2 pages.
  • Tell why your grades were low or justify any other shortcoming (if any)
    • If there are negative points in your profile, like low grades or maybe a reappear or detention, then you can justify them here. You can explain the circumstances which forced that result.
    • The admission committee is not looking for perfect candidates. Everybody make mistakes but you have to show you learnt from them and they made you a stronger person.
    • Don’t shy away from mentioning failures but you should have something to show that taught you and as a result, you performed better the next time.
  • Read the problem statement carefully
    • By problem statement, I mean the page where the university asks for an SOP.
    • Some universities might ask specific questions which your SOP should answer.
    • Some may put some hard constraints on #words, #pages, font, font size, spacing, etc. You should cater to all those religiously and not try to be over smart.
    • Most universities won’t set these constraints but you should check for these.


A Good Strategy to Follow

Now that you know what all to take care, I would like to tell you a few ideas which you can use to structure your SOP and give it a good shape. A wise man once said “If I’m given 45 minutes to cut a tree, I’ll spend the first 30 minutes sharpening my ax!” Well, planning and thinking are as important in an SOP as actual writing. Now that we have writing tips, lets get some planning tips. This might be a good strategy:

  1. Start by listing down all your experiences on a whiteboard (you can use a paper of MS office or any other means). Start from undergrad, year by year, list down everything you did and what skills are getting reflected in each of those experiences.
    • You should write down every bit of you. Its like a laundry list from where we’ll pick and choose the experiences which we want to write in our SOP.
    • Note that this list will be in chronological order but we need not maintain this order in the SOP. That’s where our creativity comes in.
  2. Next, you should think about a story. Typically an SOP will have ~10 paragraphs. So you have to create an overview of your SOP using the points you have written. Remember you need to justify your marriage! So you have to make a good case for it or else you lose the girl 😉
    • By story I mean an outline of each paragraph, i.e. what key information will be conveyed in each of those paragraphs. Trust me this outline will help you immensely. Once you have the full text, its difficult to edit it and make a coherent story. Its a lot easier if you have the story first.
    • Let me give an example story, which is chronological:
      1. Opening para – Why I want to be a part of this program? It should catch the eye of the reader.
      2. A summary of how my background will help me in this program, what I want to do in the future and how the program will help me achieve my goals.
      3. How my undergraduate curriculum allowed me to gain the strong fundamentals required for pursuing the course.
      4. Not only curriculum, I had other practical experiences during undergrad. Experience 1 and what skills it shows..
      5. Supporting experience #2 at undergrad + the skills it shows..
      6. Supporting experience #3 + skills it shows..
      7. How I continued to develop my skills during professional experiences?
      8. Another paragraph on professional experience…
      9. What particular aspects of the program I like? What courses I intend to take, extra curricular activities.
      10. Why this particular university? what’s so special about it? A closing note thanking the admission committee.
    • This is just a sample story. The idea is that there has to be flow of information. Every paragraph should have an objective. It should answer a particular question. Don’t jumble up information. Talk about one thing at a time.
  3. Write a first draft based on that outline, i.e. complete each paragraph such that it answers the question/key point you’ve decided while writing the story.
    • Don’t think about word limit right now. Just use the points you wrote in step #1 and fill the outline. Don’t worry even if you write 5 or even more pages. Make sure you put every information in.
  4. Get Feedback and Iterate
    • This is the most important step. First thing is to read it yourself and improve upon it. You’ll easily be able to do atleast 2 rounds of updates on your own. Try to get it around the 2 page mark.
    • Then, take feedback from others, your friends, colleagues, seniors, whoever you can find. Just make sure that person has some experience with SOPs. You’ll get some good points for sure.
    • Incorporate all the feedback which you feel is right. You may have to change the story your original story as well. But do so first change the outline and then change the paragraphs as per the outline.
    • I had somewhere between 20-30 rounds of review and update before I finalized my SOP. Even then while applying for a new university, I found mistakes in my most recent SOP.


Some More Advice

I know I’ve already spoken a lot about SOPs but these are the last set of precautions/things to take care.

  • Don’t use 1 SOP for every university
    • SOPs have to be different for each university
    • The university specific paragraph will obviously differ but if you’re applying for different kind of courses, then your SOP will vary slightly
    • For example, applying for MS in Analytics, MS in CS with ML specialization, MS in OR will require slightly different SOPs. You’ve to understand what knowledge the program requires and you have to focus on that.
    • Your experiences will be the same but the skills which you try to highlight will differ, the experiences which should come first will differ depending on the skill to prioritize.
    • Just give it a good though, it should work out.
  • Don’t ask someone else to write your SOP
    • No one can write your SOP as effectively as you can.
    • There are consultants which will ask you to send their details in a form. They will compile that and write an SOP but its not going to be good in most cases. Its good to take help but in getting it reviewed and not getting it completely written.
    • Another advantage is that if you write it yourself, it’ll be aligned with your writing style. If you have a 3 in AWA in GRE and you write a flamboyant SOP, then it’ll definitely raise doubts that it was written by someone else.
  • You cannot write an SOP overnight
    • Don’t think that you’ll do some last minute work and come up with a good SOP.
    • It requires time. I would say atleast a month if not two. That’s because getting it reviewed depends on someone else and he/she might take time.
    • Another important thing is to give yourself time. If you spend a few hours on your SOP in a week, then you’ll be too much into it that you won’t be able to see what’s going wrong. So you have to give it a break and start it again after a week. Trust me you’ll find all sorts of silly mistakes then.
  • Beware of spellings and grammar
    • Grammatical and spelling mistakes is the last thing you would want in your SOP.
    • Admission committee takes this very seriously and it can harm you badly.


Resume/Curriculum Vitae

Moving on to another important part of the application – the Resume! You would have written a resume/CV during your undergrad placement season or even later if you have worked in the industry. Its not very different from that but you have to take care of a few things.

  • Format
    • This is important as it gives an overall visual appeal to your resume.
    • Many people choose a 1-page format but you can even use 2 as long as it is clean and the space is used wisely. I personally feel that 1 page becomes too cluttered and I designed a cleaner 2 page format for myself.
    • If you think that you have content which doesn’t even fit in 2 pages, there is something wrong with your resume. Either the format or the content is not well defined.
  • Give details for names which are not world-recognized
    • Whenever you mention your college or your company’s name, you should give an idea about its reputation and status.
    • For instance, I’m a graduate from NSIT, Delhi and I might right “NSIT, Top 10 pan India” which shows my college is ranked in top 10. You can also place a link nearby to the website which justifies the rankings.
    • Another example could be when I mention AV, I will write – Analytics Vidhya (AV) | Rated #2 most visited analytics website by Alexa
    • If I mention an MNC, I can write something like IMS Health India | IMS CG Asia | # 7 (Vault) Healthcare Consulting – Asia Pacific 
    • These are all examples from my profile. These should give you an idea of how to present the organization where you have worked or studied.
  • Use Action Words
    • These are words which say that you have done something. These come handy when you are explaining some of your experiences
    • You can find many lists online, for instance this one from UC Berkeley.
    • Beware that you should not over-use them. It shouldn’t look that you are just writing for the sake of it. Use only when you have done something
  • Focus on what you have done
    • Whenever you are part of a team, you should have an emphasis on your role and your contribution.
    • Just mentioning the team’s achievements will be of little help as the reader is still not sure what you gained out of the experience.
  • Mention Dates
    • Writing the duration of your experiences is essential as it helps the reader gauge your involvement
    • Try to be as complete as possible in terms of the timeline
  • Specify metrics of judging performance
    • Like I said earlier during SOP, the same rule applies here.
    • For instance, if I write that I wrote 15 articles for Analytics Vidhya, it sounds incomplete as the reader has no idea how good they were. But if I add details like they recorded ~250,000 page views on Google Analytics and the best one was close to 30K page views, then it makes more sense.
  • Don’t give over-emphasis to MOOCs (online courses)
    • These days almost everyone takes these courses but you should not mention them more than the name.
    • If it really aligns with the profile, then you can give 1 line details but not more than that in most cases.
  • Be specific about hobbies 
    • Every part of the resume matters, even hobbies
    • Don’t just write I like to read, listen music, sing. Give details. I like to read novels with an emphasis on auto-biographies and science fiction. If you mention music then specify genre and favourite artists.
    • You can have other hobbies as well like post-match analysis in football or cricket, etc. Try to be different and be specific.


Letter of Recommendation (LOR)

LOR are letters from your professor or professional supervisors who have supervised/guided you in academic or professional capacities. It’s generally recommended to take LOR from people who know you for atleast 1 year. But if it really makes the profile stronger, you can take it from internship supervisors with 2-3 months of experience. But it should just be in one case not all.

Most universities would require 3 LORs. They might/might-not specify the split between academic and professional LOR. Some universities may specify 2 academic and 1 professional LOR while others might not. You should take LORs from people who were with you from experiences more related to analytics/data science.

For instance, I am from a manufacturing engineering background so I chose 1 academic and 2 professional. Even if the university says it needs 2 academic, you can talk to them and they are mostly flexible about it.

In India, its a sad thing but mostly students have to write a draft of the LOR and the professors make minor adjustments. But you should take care of the following if you or your professor write it:

  • Provide anecdotes for supporting the claims of skills which a student possess.
    • Don’t just say he is punctual, hard working, intelligent, has strong mathematics fundamentals.
    • Give instance which made you feel that way. For example,
      • The student is hard-working as he completed all the pre-readings and submitted assignments on time
      • strong mathematical fundamentals can be shown in one of the projects done
      • Other skills might get reflected in other activities of the student
  • Provide metrics
    • The more details provided the better
  • Compare the candidate with others similar to him
    • Professor/professionals can rate him with his peers or past students/colleagues in similar role
    • It’s good to mention the “top X%” in which the student lies
  • Mention shortcomings and scope of improvement
    • Since we are humans, everyone has some drawbacks as well
    • Its good to write the areas which require improvement. This shows that the opinion presented is honest.
    • But don’t mention shortcomings like “candidate it too hard working”. Make it sound real.


Transcripts and Other Formalities

A transcript is nothing but an official document from your universities containing attested copies of your marksheets and final degree, if you have it already. The documents are sealed in an envelop with registrar’s signature on the seal. Your undergrad college will do the needful once you inform them that you need a transcript.

Some universities can have other formalities as well. For example:

  • Additional Essays
    • Apart from SOP, some universities may ask for a Personal History Statement as well. In this essay, you have to describe your personal background. The idea is to show what social and cultural barriers you faced during your education and how you overcame them.
    • There can be additional essays as well which’ll depend on case to case.
  • Sending Application Material by Post
    • Although the lion’s share of universities will ask you to upload documents at the time of applying, some might ask you to send hardcopies of transcript along with complete application.
    • You should take special care that you dispatch it alteast a week in advance so that there is sufficient time even after delays.
  • Sending GRE and TOEFL Score reports
    • You can send these scores to 4 universities for free along with the exam. But those 4 universities have to be specified at the time of taking the exam.
    • There are high chances that you won’t have a clear idea about which universities you’ll be applying to and you’ll need to send these reports later. You should send them as soon as you university list is ready because it can even take around 2 weeks for the scores to reach the university.
    • The universities are however not so paranoid about receiving these scores even after the deadline. But its better to be punctual as it shows your planning.


Phase 4: Selecting from Admits & Flying Off to US

Now that the applications are made, its time to wait for the results.

This can be very daunting at times because some universities can delay the result by a long time. I have even seen people getting admits in June. But most of the replies should come around April-May. If things get further delayed, most of the universities will tell you that you are on a waiting list.

Once you have the admits and rejects, its time to take the final decision. Now its time to explore those programs in a lot more detail. Some of the following can help:

  • Search for current/past students on LinkedIn and send them InMails asking further information. While talking to someone, you should have specific questions along with a general feedback about the program.
  • Look at the curriculum and electives in detail and make comparison charts.
  • Look at the tuition and living expense. The living expense can vary dramatically from location to location. For instance, one of my friend in San Diego has a living expense of around $500 per month all inclusive. If you move to New York, the same skyrockets up to $1750-$2000 per month. That’s a huge difference so you should take these things into account.
  • See which companies people generally get into after the program and benchmark it against your expectations.

Universities generally give around 2-3 weeks to make a decision. You might have to take a decision when other results are still awaited. There might even be an offer acceptance fee ($1000-$20000) which is non-refundable if you reject the offer later. But that risk has to be taken and there is little you can do about it.

After you select the college, there are many more formalities which you’ve to be prepared for. Some of these are:

  • Sending the official transcript, if you’ve not already done so.
  • Preparing financial documents to send to the university requesting the i20 form. i20 is an invitation that the university sends which is required for getting a student visa. This can be a very tedious task and can take a couple of weeks of effort easily.
  • Getting VISA is another task. The waiting time at different consulates vary from 15 – 40 days and you should plan everything accordingly.
  • Remember to book flights on time or else you’ll end up paying more money later.
  • Getting accommodation can be a big pain if university doesn’t provide it for all.

There are many small things which are required before you can finally start packing your bags and board your flight.


End Notes

I hope this article helped in you in deciding your career move to US. You can say, it is an honest review of the complete process from my side. I faced enough troubles in the whole process and I expect this article will help you overcome many of them.

In this article, I took you through the entire journey from thinking about going for an MS program in US to taking the final decision and completing all formalities.

If you have any other thoughts or comments, please feel free to drop me a note below. I’ll be happy to discuss further.


  • Rahul Sharma says:

    Very Well described. I am also going to pursue MS in Data Science. Can i get your email id?

  • Nawaz says:

    I am a working professional and looking for some online courses instead.Would you recommend “Data Analyst Nanodegree” from udacity?

    • Aarshay Jain says:

      I haven’t used Udacity much. The syllabus looks pretty cool though. You can also do the “Machine Learning Engineer” Nanodegree after that.

  • Gaurav says:

    Any good online master’s programs in data science?

  • Swanand says:

    Informative ! I am also planning to pursue Ms in data science from columbia university ..So keep posting more articles related to same ..

  • Farhan Hussain says:

    Thanks Aarshay. Very detailed and to the point.

  • Utsav Maniar says:

    Hello AArshay,

    How important are the research papers for getting admission in MS in Data Science and also the work experience? Thanks.

    • Aarshay Jain says:

      It really depends on what career path you want to pursue. If you wanna be a researcher then you should apply to programs with such inclination and research papers will be important there. Similarly for the professional part.

  • Tarun says:

    Hi Aarshay

    Thanks for the detailed explanation of the process. Although I have a question regarding UC Berkley. How is the data science program there and also what is required to attain the full time scholarship.


    • Aarshay Jain says:

      Its an online program. I don’t know much but I think there are rare scholarship options in such programs.

  • Kunal Dash says:

    Very detailed and insightful comments. Very well laid out. This is basically a go to tome for anyone interested remotely in trying to make a career in data science and analytics.

  • Lakshmi says:

    Excellent guide for anyone who wants to prepare for higher studies, not just data science, in US. Thanks for detailing it out so well. All the best for your education in Colombia and your analytics career.

  • Kunal Dash says:

    Hello Aarshay/(also if Kunal J might be interested to comment),

    Here is my question. We have a lot of courses on various topics in the form of MOOCs. These could be titled similarly or diversely like data science, data analytics, data analysis, business analytics, machine learning and data mining to name a few. My question is whether there is a way to rank the following MOOCs in terms of difficulty for the uninitiated and also in terms of practical usage or application in the industry or when you are out there. The MOOCs that I am referring to are the following:

    1. From Coursera:
    – Data Science from Johns Hopkins
    – Data Mining from Illinois
    – Data Science at Scale from Univ of Washington
    – Applied Data Science with Python from the Univ of Michigan
    – Executive Data Science from Johns Hopkins
    – Process Mining from Eindhoven
    – Business Analytics from Univ of Pennsylvania
    – Strategic Business Analytics from ESSC Business School
    – Excel to MySQL from Duke Univ
    2. From Edx
    – Data Science and Engineering with Apache Spark
    – Data Science and Analytics in Context by Columbia Univ
    – Marketing Analytics by Berkley, California
    3. Any other comparable ones!!

    Any insights will be greatly appreciated.

    • Aarshay Jain says:

      That seems to be a hard question. Turns out, I haven’t taken any of these courses 😛 I think it’ll take another full article to review all these courses 😀

      I like the Machine Learning Specialization by Un Of Washington on Coursera. The one with Carlos Guestrin (Turi founder).

      I’m sure kunal will have more ideas and he can help you out here. Otherwise, best would be to open these courses, look at syllabus, read reviews of past sessions and see if it works for you. Honestly, I don’t think a ranking makes sense here because these appear to serve different objectives. It all depends on what you want to learn.

  • Oluwadara says:

    Thanks Aarshay for this well-detailed outline.

  • Prem chand says:

    Thanks Aarshay for this vivid article, you nailed it 🙂

  • Franco says:

    Hi Aarshay,
    In the article you talked only about data science programs and analytics programs, in terms of which you suggest to take the GRE test, But according to my knowledge, most of the master programs that can be connected to big data are set in business schools, which prefer a GMAT score. And I am a finance major so I think I will not be accepted by a program that is too tecnical. So I chose to take the GMAT. Do you think this is OK? And another question, what if I put nothing about my MOOC courses (Python and maybe there wiil be more) and writes few sentences about them in my SOP or Personal statement? Is that a good idea? Cuz I really don’t know in which category of my CV shoud I put them haha.Thank you very much!

    • Aarshay Jain says:

      I would not say most but many are part of the business school. Actually, in most of the cases both GRE and GMAT Scores are acceptable for these programs. So you should good with a GMAT as well.

      I didn’t get your second question fully. So please get back to me if my response doesn’t answer your question. I generally put MOOCs under “Additional Courses” or “Additional Professional Development Activities”. I would not write more than the name in a CV. Mentioning them in SOP or personal statement can be justified only if it really shows an important skill/achievement. Otherwise you might be better off writing how you applied the learnings from the MOOCs you’ve taken.

      Hope this helps! All the best!

      • Franco says:

        Yes that’s exactly what I mean in the second question! Thank you! In your opinion, what is the difference between busienss analytics programs (100% of them are in business schools) and data science or analytics programs (90% of them are not in business school, I assume). Is there any difference in career path? One of the difference I’ve seen is that most of the programs that are not in the business preffer applicants with more technical skills and most of the accepted students had engineering or mathmatical majors in undergrad. So what is the differce exactly? Thank you again for your help!

        • Aarshay Jain says:

          Yeah its like what you mentioned. Business analytics programs are more business oriented. But even analytics programs can be high on business side. you should really check the curriculum and not just go by the name.

          The requirements from applicants will also depend on the curriculum. So you should just see how suited are you to take that curriculum. If you feel comfortable, there are high changes that your background won’t be a problem. But if you yourself feel thats not what you’re made for, the university will definitely reject you because you will not be able to justify something you yourself don’t believe in.

  • Medha says:

    Hi , Aarshay , good article. what is the option after 3 years undergrad in economics in India, if I want to do Ms in Data science?

    • Aarshay Jain says:

      I think you can pursue these programs because they are open to people from all backgrounds. However, some universities might have an issue with a 3yr education thing and you might have to work for some time to overcome that. I’m not too sure about that so I recommend that you check this out with the specific universities you are planning to apply to.

  • Revati Joshi says:

    Hi Aarshay,

    Great article! Thanks a lot for this info 🙂
    However I have some questions regarding the prior work experience being considered.
    You mentioned that the profile plays an importantrole along with a good score in GRE. Since I have completed my Masters in Computer Applications from NIT Surathkal (with Data mining as an elective) , and having done my internship with Morgan Stanley for 6 months in Machine Learning, how much more experience can I consider good enough to start my application process?
    Any suggestions for MS+PhD in Data science? Do you have any idea regarding what is the current scenario with PhD fundings?
    You also have had conversations with seniors as you mentioned here. Wjatis the average experience level of the applicants there?
    I believe that the qualification and experience both would be a key combination, what would you suggest?
    Thanks in advance and all the best to you 🙂

    • Aarshay Jain says:

      Yes you got it right both qualification and experience matter. The thing is that these programs have a mixed class profile consisting of people right have their undergrad, ones with 1-2 yr exp, with 2-5 yr exp and even with 5+ years of experience. So you can apply anytime. But you should note that the average is around 2yrs so having experience definitely increases your odds but if you undergrad experience is highly related, you can get it directly as well.

      Regarding PhDs, I don’t think many universities will offer something like a PhD in Data Science. Mostly it’ll be like PhD in CS with Data Science specialization. But I guess PhD programs will definitely come up in future.

      Hope this helps!

  • Nitish Mahajan says:

    Hi Arshlay

    I am looking to pursue MBA with concentration in Business Analytics and have recently attended QS MBA fair for the same. Considering the expenses of an MBA to be taken into account, is is safe if I only opt for MS in Business Analytics.


    • Aarshay Jain says:

      In my opinion MBD and MS in BA prepare you for kinda different career paths. MBA will take you more into managerial roles in your current domain and MSBA will help you get started with business analytics. Also, the profile requirement for getting into these are widely different.

      You should really consider what career path you want and then take a call.

  • […] How to start applying for Analytics / Data Science Masters in the US Universities? – If its blunt and boring like the 100 other SOPs the person reads everyday … I’m given 45 … […]

  • Rushkesh says:

    Hi Aarshay,

    Very good article. It gives lot of info for aspirants who will be trying to pursue MS in Data Science.
    I have one question if we do not have any project done on data analytics in undergraduate studies does it matter for admission in Masters in Data science.

    • Aarshay Jain says:

      Thanks Rushkesh.

      I reckon it’ll matter if you’re applying right after undergrad. It would be a better idea to get some experience in this domain and then apply. But it again depends. If you can show that the knowledge you have mustered in your projects can be directly used, it can help. Many people get into these programs right after undergrad but without related experience, getting into a good one might be a challenge.

  • Utsav Maniar says:

    Hello Aarshay,

    Very good article. Keep posting articles like these during your MS as well, so that MS aspirants like me can have idea about what to aspect in MS and how to prepare for applying to the same. And we can know about your experience during MS and beyond as well. Thank you.

    • Aarsha Jain says:

      Sure I’ll try but I’m getting a feeling its going to be really difficult given the high workload here..

  • gajesh jain says:


    Any idea about PhD programme

    Gajesh jain

  • Franco says:

    Hi Aarshay,
    What is your opinion of both short-term career goal and long-term career goal if I want to apply for a Business Analytics program? I only know that you can be a business analyst in companies such as Walmart after graduation. ( I think those positions in IT companies such as GOOGLE is moe technical and thus more suitable for Data Science students like you ?) Is there any other short term goal examples? And how about long term goal. Since business analytics is a relatively new area, most graduates do not have much experience in this area. So I don’t know what will or what can they become after 10 years’ career. I don’t know what to write about this part in my personal statement, But it asks me to write 400 words… Do you have any idea? Thank you!!!

  • Subir says:

    Hey Aarshay,
    Thank you for sharing your experience. It was really helpful. I would like to know about Masters option in Statistics in India. Do we have good institute from where i can pursue masters.
    Thanks in Advance

  • Sai says:

    Hello Aarshay,
    I’m a Mechanical Engineering graduate with B2B sales experience. I’ve not done anything related to analytics before, except I had taken some courses like Engineering Finance and OR. Can I get into any university for MSBA?

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