How I Got Into Columbia University For MS Data Science?

Hey! Who are you, what are you currently doing and what is your background?

My name is Riddhi Dinesh Oza, and I am currently pursuing a Master’s in Data Science at Columbia University. I have a background in Computer Engineering from the University of Mumbai, specifically from Father Conceicao Rodrigues College of Engineering.

Internships during my undergraduate studies played a pivotal role in shaping my profile. For those pursuing master’s programs, internships are essential as they strengthen your application and align it with the program’s focus. I highly recommend targeting internships that complement your intended master’s specialization.

I gained hands-on experience through various internships, starting with a training-cum-internship at One Stop AI, where I worked on Natural Language Processing (NLP), automatic speech recognition, and audio analysis. I also contributed as a web developer in my college’s technical team, a versatile skill that helped me create dashboards for data analysis and software engineering applications. Additionally, I worked on machine learning projects, including a computer vision-based tool to detect the attention span of autistic children. My experience as a full-stack developer at a startup further honed my skills, where I used React to build dashboards and an order tracking module.

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How did you decide that you wanted to pursue an MS in the US?

I never thought I would be coming to the US until I actually started applying. It was my dad who inspired me. He told me that once you start earning, it becomes very difficult to return to a learning phase. He encouraged me to complete my education first so I could focus on work and other priorities later. 

As for choosing Data Science, I noticed that many people opt for a Master’s in Computer Science and then specialize in Data Science later. I didn’t want to study the same subjects I had already covered during my four years of undergraduate study in Computer Science. Over time, I realized that my passion lies in the data science domain, which is why I chose a Master’s in Data Science.

How did you start your application preparation; can you throw some light on profile building, GRE, LORs and SOPs?

GRE/TOEFL

Regarding preparation for GRE, LORs, and SOPs, this process can be subjective. During the pandemic, many universities waived the GRE requirement. I still prepared for the GRE on my own without any coaching. While it’s not overly difficult, it does require time and mental effort. I prepared for one month, studying seven to eight hours a day. 

I scored 314 out of 340 on the GRE, which I think is a decent score—not exceptional, but good enough to get me into Columbia. Mock tests were an important part of my preparation. Interestingly, I never scored above 300 on mock tests, but I managed a 314 on the actual exam. My split was 158 in verbal and slightly lower in quant than expected because I wasn’t fully prepared for some topics within the given time limit. In the analytical writing section, I scored a 4.0 out of 6.0.

SOP

As for the SOP, it’s one of the most crucial aspects of your application. No matter what people say about using tools like ChatGPT, your SOP should be your own story. It needs to demonstrate that everything you’ve done so far aligns with the master’s program you’re applying for. A good way to approach this is to create a document where you list everything you’ve done—projects, internships, challenges, and achievements—and then identify unique aspects of your profile.

When writing the SOP, talk about your struggles and how you overcame them. For example, if you had a low GPA, explain why. Maybe you were working on a startup or dealing with personal issues. Highlight how you managed to overcome those challenges and improve. It’s also important to articulate what you want to achieve from the master’s program. Of course, financial growth is a factor, but explain how you plan to use your degree for a larger purpose. For me, it was about using technology for the betterment of society.

LOR

LORs are another critical part of your application. I recommend having a balanced mix of academic and professional references. I had three LORs—two from professors under whom I worked on mini-projects and my final project, and one from the founder of the company where I interned. 

Timelines

In terms of my timeline, I started preparing for the GRE from mid-June to mid-July. I took the GRE in August and the TOEFL in the first week of September. I then focused on applications, completing all of them by around October 17th or 20th. After that, I started receiving admits and rejections from November through March.

What colleges did you apply for and what was the result?

I applied to 10 universities as below.

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Can you tell us more about the course and what the learning outcomes are?

Deciding between universities was a big challenge, especially when you have multiple admits. My final choice came down to NYU and Columbia. NYU was my dream university. However, when comparing the two, tuition fees became an important factor since both were located in the same area. People often mention how Ivy League universities have very high fees, and while that’s true, I found the costs for Columbia and NYU to be almost the same. 

Ultimately, I thought about the additional value. If I was going to spend that much money, getting the Ivy League tag and attending a university with Columbia’s reputation seemed like the better choice. That’s how I decided on Columbia over NYU.

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What is the cost of tuition and cost of living, and how are you planning to fund your studies?

Pursuing a master’s degree is a sensitive decision, especially if you don’t come from an ultra-rich family. It’s financially overwhelming for both parents and students, but I believe it’s one of the best decisions you can make. 

Regarding the cost of tuition, it’s approximately $102,673, which comes to around 1.03 crore INR. This figure is mentioned on the I-20 form. Including living expenses, it can be slightly higher, but this is a good estimate.

Scholarships are generally not available for ambitious or top-tier universities. Universities that are less recognized may offer scholarships to attract students, but for schools like Columbia, you won’t get scholarships just because you’ve been admitted. Teaching Assistantships (TAs) and Research Assistantships (RAs) are available, and they pay around $20–22 per hour. However, securing these positions depends on your efforts. You need to be proactive, contact professors, and act quickly. If you’re keen on earning through these opportunities, you have to do the groundwork.

As for loans, choosing the right provider is critical as it shapes your financial future. Many suggest ICICI Bank because they don’t require collateral, but their interest rate is around 11.75%. I opted for a loan from Union Bank of India, which charges me around 9.5%. The difference in interest rates, especially when compounded, is significant. For me, it was about not overburdening myself with repayment pressures. If you’re from a middle-class or upper-middle-class family, I recommend carefully considering the interest rate and overall terms of the loan. That’s how I decided on Union Bank. 

What are the job opportunities after master’s?

I’m currently in a situation where I need to apply for a lot of roles, so the future really depends on individual effort and circumstances. As far as internships and stipends are concerned, it’s very subjective. There isn’t a specific answer for this—no one can guarantee a certain stipend or internship opportunity. Similarly, when it comes to jobs and salaries, it’s highly variable. There’s no assurance that graduating from a particular university will get you a specific salary like $100,000 per annum; it entirely depends on your skills, the roles you apply for, and the job market.

For entry-level roles, people often say it’s tough to get a data scientist job as a fresher. Many PhD candidates also apply for data science positions, which makes the competition intense. Companies often prefer hiring freshers for software development engineer (SDE) roles instead. They see SDE positions as more forgiving, where mistakes can be fixed without much impact, unlike data-related roles, which require handling sensitive and critical information. That’s why landing a data scientist job as a fresher is quite challenging.

Any final words of advice for anyone who aspires to be where you currently are?

First, reach out to people on LinkedIn. Speak to them as much as you can and follow up with them. The more you speak, the more clarity you’ll get. This approach has helped me a lot. Even if they don’t reply immediately, they will eventually, maybe after a week. Trust me, everyone understands the pain because they’ve gone through the same process. It’s like a loop—when people approach me now, my LinkedIn is full of messages like “I’m applying” or “I need guidance.” I make sure to reply to each one of them because I was once in the same position.

Second, focus on building your profile. Make sure your resume is strong. Don’t use standard templates; instead, highlight the impact you’ve created in your roles. Follow Google’s formula for crafting impact statements; it’s incredibly helpful. Also, maintain a good CGPA. In my case, I’m pretty sure I got into Columbia not because of my GRE score but because of my CGPA. Many students here have GRE scores of 333 or 335, and mine was only 314. However, my CGPA was 9.98 when I applied, and that made a significant difference. So, prioritize your academics.

Additionally, save money during the application process. It’s expensive, and the costs can easily add up to 1.5–2 lakhs when you include application fees, GRE, TOEFL, and other expenses. Maintain an Excel sheet to track everything, and try to get application fee waivers wherever possible.

Lastly, accommodation is often underrated but incredibly important. Finding good roommates is a blessing because they’ll become your family away from home. Choose wisely and ensure you connect with them beforehand. Be prepared to grind—this journey is not easy, and the struggle is real. But trust the process, and it will be worth it.

Throughout the process what were some helpful resources, tools and books you used?

Look for free GRE books or other materials, and you’ll come across many helpful drive links. Unless you actively search, you won’t find what you need. As far as YouTube is concerned, Tested Tutor was incredibly helpful for me. 

For university selection, I had a counselor. My counselors were from GoGenius, and I recommend them. This isn’t an advertisement—it’s my genuine experience. If you’re someone who is new to the process and doesn’t have family or friends who have studied abroad, these counselors provide much-needed clarity. If you can manage everything on your own, that’s even better, but for those who feel lost, I highly recommend seeking guidance.

For accommodation, I primarily used StreetEasy and Zillow. It’s a great tool, and honestly, I didn’t rely on Facebook or similar platforms—I stuck to StreetEasy because it worked well for me.

For travel and visa preparations, the first thing is to shortlist universities early so you can book your tickets in advance. This can save you thousands. If you delay shortlisting and decision-making, it can push back the entire process, making everything more expensive and time-consuming. Once you receive an admit, decide within a week.

Regarding loans, I recommend government banks like Union Bank of India and State Bank of India. These are reliable options for education loans. Make sure you understand the entire loan process thoroughly. It’s not easy, so take the time to go over the terms, create your account, and manage everything independently. 

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