How I Got Into Georgia Tech For MS Analytics?

---

---

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

I’m Vaani, and I completed my undergraduate degree in Electronics and Instrumentation Engineering at BITS. After that, I pursued a Master’s in Analytics (Computational Track) at Georgia Tech. Right now, I’m working as a Quant Analyst at Bank of America.

During my third year of undergrad, I worked on a project with a professor where I used NLP techniques to summarize and analyze the sentiment of certain documents. That experience sparked my interest in data science, a field I had not previously considered pursuing. In my final year, I built on that interest by interning for six months with an NLP research team at Genpact, working on both research and client projects.

After graduating, I worked for a year at a fintech company in India,  InCred Financial Services, as an Analytics Specialist. The role wasn’t heavily focused on machine learning but involved a lot of data analysis and insights generation.

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

I decided to pursue a master’s degree because I wanted to deepen my technical expertise in working with data—whether it was analyzing it to generate insights or building products that leveraged data for other teams. My experiences in India made me realize how much I enjoyed this space, and a master’s program seemed like the best way to gain a structured, in-depth understanding of advanced topics.

Choosing to study in the US was more of a personal decision. I wanted to move to the US, and since I had always planned to pursue higher studies, it felt natural to do so here. While I don’t have a singular, definitive reason beyond that, it was a choice that made the most sense for me.

As for selecting analytics, the distinction between “data science” and “analytics” is often blurred, with many programs using the terms interchangeably. Although my program was officially titled a Master’s in Analytics, it was highly technical and focused on machine learning. My priority was finding a program that aligned with my learning goals, so I carefully reviewed various curriculums before deciding on Georgia Tech. I didn’t choose it as a backup—I actively selected it because it provided exactly what I was looking for.

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

At the time of applying for my master’s, I had only been working full-time for a couple of months, so I didn’t emphasize my work experience in my application. Instead, I focused on my internships and college projects. Most of my academic projects were under a finance professor, and while they weren’t highly technical, they involved problem-solving and analytical thinking. I used these experiences to showcase my skills.

My internships provided stronger data science experience, so I highlighted them in my application. However, I kept my SOP factual and avoided exaggeration. Since my CGPA was on the lower side, I ensured that other aspects of my profile, like my statement of purpose and test scores, were strong.

GRE/TOEFL

I took the GMAT and scored 730 (Quant: 50/51, Verbal: ~39). Since my CGPA wasn’t particularly high, I saw my GMAT score as an important standardized metric that could strengthen my application. While I’m not sure how much weight it carried, I treated it as a critical component.

I originally took the GMAT because I had considered doing an MBA. However, during my final year, I realized that I was more interested in data science. Since most of the schools I applied to accepted the GMAT, I decided to proceed with it rather than taking the GRE.

SOP

Given my non-traditional background, my SOP played a crucial role in my application. I spent a couple of months refining it, making 10–15 drafts, and getting multiple reviews. My SOP focused on:

• My past experiences, including projects and internships
• Why I needed a master’s degree and why this school would be the right place to do it
• My career goals and what I hoped to achieve

Since admissions committees value clarity of purpose, I made sure to clearly articulate why I was pursuing a master’s and how my experiences aligned with my goals. I also researched each university thoroughly, going beyond just listing courses and clubs. For instance, if I mentioned a club, I would check their social media to understand their activities and how I could contribute. This level of detail made my SOP more genuine and compelling.

Additionally, since my undergraduate degree was unrelated to CS, I used my SOP to explain my transition into data science. I demonstrated that while I lacked formal CS education, I had taken steps to bridge the gap through projects and internships. I also framed my fintech and finance experience as an asset, showing how it aligned with my future goals.

LOR

I had four LORs in total but didn’t use all of them for every application. My primary recommenders were:

• A college professor
• A professor from another university with whom I did a project
• My internship manager from my final-year internship

Since I had only been at my full-time job for a short time, I didn’t ask my current manager for a recommendation. Instead, I relied on people who had worked with me longer and could provide stronger endorsements of my abilities. One of my professional LORs wasn’t directly related to data science, so I was selective about where I used it.

Timelines

GMAT Preparation: Started in April 2021, took the exam in 3–4 months.

Application Work: Focused on SOPs and materials from August to October 2021.

Submission: Most applications were submitted in November–December 2021, with the latest in January 2022.

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

I applied to 10 universities as below.

Note from TheGradPost: To view the below list of ambitious, moderate and safe universities, please subscribe!

Hey, get access to premium content by subscribing to TheGradPost!




Email

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

The reason I liked Georgia Tech so much was the flexibility of the program. They offer three tracks that you can opt for, but the great thing is that you’re not bound to the track you pick. Eventually, you’ll satisfy some track requirements based on the courses you take, but you have the freedom to explore. With a wide range of electives to choose from, almost all students in the program took courses across the Computer Science School, the Business School, and the Industrial Systems School. This flexibility allows you to explore different fields and figure out your direction as you go. For my track, I chose the Computational track, which is essentially their core technical data science track. I focused on machine learning courses through that path.

Another factor that attracted me to Georgia Tech was the program duration. Although it’s publicized as a one-year program, you have the option to extend it to a year and a half. I liked that flexibility because it gives extra time to search for a job, complete an internship, and use that experience to decide on the right career path. With these two factors in mind, I chose Georgia Tech.

My cohort size was around 100 to 115 students. One great thing about Georgia Tech is how transparent they are with their statistics, including employment rates. Their website is really helpful—you can see the cohort size, students’ backgrounds, years of experience, where they end up after graduation, and even the salary packages they receive.

---

---

What is the cost of tuition and cost of living for the program?

Tuition, without any scholarships or financial aid, is approximately $50,000 for one and a half years. One of the great things about Georgia Tech is that TA positions are relatively easy to get compared to other universities. While Georgia Tech doesn’t offer scholarships at the time of admission, they do provide TA positions, which can cover  a significant portion of your tuition. 

Tuition is based on a credit system. To maintain full-time student status, you need to take at least 12 credits per semester, which usually means four courses. However, a TAship counts for three credits, so you can take three courses and a TAship, and that still meets the requirement. If you take four or more courses, the tuition is fixed, meaning that whether you take four, five, six, or even seven courses, you pay the same amount as you would for four.

As for the cost of living, rent varies depending on whether you get a private or shared room. If you have your own room, it’s  $1100 on average (however rent has been increasing). If you’re sharing, you might pay around $600 on average . This doesn’t include additional utilities like Wi-Fi and electricity, which depend on where you stay. Other expenses like groceries, transportation, and entertainment vary based on lifestyle, but a few hundred dollars per month is a reasonable estimate.

What does the future after master’s look like?

Looking for a job, especially in the current tech and data science market, is definitely challenging. It’s completely normal to send out hundreds of applications and hear back from only a handful. While most people apply online, getting a referral or having someone hand your resume directly to a hiring manager can help. Personally, referrals haven’t worked for me, but I know others who have had success with them. Relying solely on ATS systems can be unpredictable, so any way to bypass them is worth trying.

For internships, I started applying in August when my program was just starting, and I think that played a big role in my success. I was fortunate to secure my internship early. my program. Finance companies, in particular, hire well in advance, so applying early can be beneficial if you’re targeting them. Georgia Tech’s internal career portal and career fairs were also useful. Career fairs can be hit or miss, but if you have a meaningful conversation with a recruiter, it can improve your chances. Some companies take resumes directly, while others provide job links exclusive to the career fair, which helped me land interviews.

For full-time roles, the process was similar but more challenging. Career fairs were much more effective for internships than full-time jobs, as companies don’t always recruit that far in advance. The ideal scenario is getting a return offer from your internship, which eliminates the stress of job hunting later, but that’s not something one can plan for. 

Getting your resume directly to a hiring manager isn’t easy, but leveraging LinkedIn connections or personal contacts can help. Georgia Tech’s MS Analytics program had its own career fair where we could hand resumes directly to hiring managers, which was another great way to bypass the standard online application process.

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

A good Statement of Purpose (SOP) is something I strongly advocate for. Regardless of your background, being able to articulate your goals clearly is crucial. I highly recommend that applicants spend a significant amount of time refining their SOP. It plays an important role in applications. Looking back, I think it would have been helpful to get more feedback on my essays.

I know many people want to apply to a large number of universities, and that’s completely fine. But it’s essential to be clear about why you’re applying to each one. Make sure that if you do get admitted, you would actually want to attend. Being honest with yourself about your choices is important.

This is slightly unrelated, but applying to multiple universities can be very expensive, with application fees averaging around $100 per school. One thing that worked well for me was attending university webinars and seminars. These sessions are meant to introduce prospective students to the program, and they often come with an application fee waiver. Attending these not only helps you save money but also allows you to ask questions and gain more insights about the program. If you’re applying to 10 universities, these waivers can easily save you  a couple hundred dollars. 

Resources Suggested by TheGradPost

For GRE/GMAT, especially for acing it in the quant session, try out Target Test Prep (TTP).

Air travel and temporary accommodations – MakeMyTrip

Help with a simpler transactions process – HDFC, SBI, ICICI Credit Cards

Connect

Linkedin – Vaani Radhakrishnan

The Grad Post is organising 100s of such case studies for students going abroad. You can have a look at the website here.

If you want to feature on my blog, lets have a quick chat! Fill out the form and I’ll contact you 🙂