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With the hustle-bustle of Day 1 of the internship season over, a lot of us are left wondering about the options that are in store in the future. There’s anxiety and a lot of stress, but we would like to remind you that there are some really great companies that are yet to come. To help you out, we’ve compiled and summarized some of the Summer Blog, written by students who interned in companies that come after Day 1. 

This is by no means an exhaustive list and you can find more of such articles on


My Intern project included three topics – Credit, fixed income, and inflation. The best thing in Finmechanics is that the work you do goes to direct deployment and is used in some way or the other. No project is a side project. The sense of responsibility we get interning here is what makes Finmechanics stand out from the rest

Morgan  Stanley

Experience of working inside a financial institution. You’ll get to learn a lot about the culture inside financial companies, and just generally, how things work. If working in a comfortable atmosphere inside a large financial company sounds enticing to you, you’ll definitely love this aspect of the job.

All in all, Morgan Stanley has been an overall positive experience for me, one in which I’ve got to learn immense amounts, and one which I’d definitely recommend to all interested juniors.


On a superficial level, my project work deals with developing a comprehensive approach for the scale-up of an early phase Active Pharmaceutical Ingredient (API) production from laboratory to commercial scale. You might know that Pharma industries generally operate at a pilot scale based on product demand. My work requires intensive research about the unit operations in  API production and build a strategy to scale up. You might consider it a desk job but we have visited all their production units. You can approach the mentor and any other employee for that matter, they are always ready to help and contribute to your work. 

Dr. Reddy

After the initial orientation and formalities at the main campus, we were allotted our separate work locations. I am posted at the Chemical Technical Operations (CTO-4) plant in Hyderabad. If you didn’t know, nearly all pharmaceutical products are made in a batch mode of production. Quite largely, my work is related to switching from batch mode of production to a continuous mode of production. My work requires me to find innovative equipment and processes and finally build a new plant from scratch.


I was assigned to the Product Commercialisation Team, which essentially looked after the entire lifecycle of the product (here, chipset) which they manufacture. My work was to implement a few features in the tools they use to track or monitor these products’ stages after they are released. Through the project, I learned about the lifecycle of the chipset and the various processes involved in its manufacture. We would have regular online meetings with people from the San Diego office who would be reviewing our progress and guiding us in our project.

Although the work is inclined towards the software side, I had regular and interesting sessions of technical training where we were taught about the various subsystems that went into the Snapdragon chipsets.


Daikin really cares about its interns. The whole internship is well planned and the interns are properly taken care of with fair enough accommodation being provided. There are regular meetings to keep themselves updated on the interns’ progress and they take a real interest in the work you do and in the ideas that pop up in your brains. My work is based on Computational Fluid Dynamics (CFD). I am expected to simulate the multiphase flow of refrigerant and it’s vapour flowing through the pipes of an Air Conditioner.

Texas Instrument

My work was on parasitic element extraction and simulation, EM/IR simulation, and timing analysis. All the work was executed on Cadence. It took a week to get acclimatized to the software and the setup as all the programs are run on LSF’s (Load Sharing Facilities). It was quite messy to work around with so many terminals and windows open, but we got used to it quickly.

Generally, we are expected to finish one problem statement in the given time frame of the intern. I was lucky to work on three of them.

Most of the projects are challenging and I had to interact with a lot of specialists for complete understanding. We are encouraged to come up with better ideas than the existing methodologies. This value for our ideas was encouraging in trying out new things within the project.


Citibank is among the top ten largest (Forbes) and the only standing global bank in the world (our floor president). We attended various sessions on how the company makes money and manages its various portfolios. So if you’re into banking and finance, here’s an opportunity to learn from the best. You are encouraged to ask for sessions on topics not covered in the planned ones (I completely made this one up, but I’m positive it’ll hold). Your project will involve machine learning so it won’t hurt to get a taste of it beforehand.

AB InBev

To give you some context, AB InBev has two offices in Bangalore: GAC (Growth Analytics Center) and the GCC (Global Capabilities Center)

My project is related to cash flow forecasting in the company’s Europe markets. Like most leading companies, AB InBev is incorporating data science into all its operations. The fact that I am the only one working on analytics in my department is a bit of a challenge. Since not many people in the office work on analytics, you’d often have to navigate your own way through the chaos.

Till now I have had to interact with several teams in the office and understand their business processes. For the remaining part of my project, I might have to get in touch with the domestic sales team in Belgium through teleconferencing. Overall, you get to know a lot about the business side of things and get exposed to people from many different backgrounds.


The initial few weeks involve brainstorming in the broad area to look at various domains in which we can work to contribute to that field. After choosing a problem we also need to defend the problem in front of other members of the Big Data Lab. The defence involves conveying why we think our problem is hard, interesting & research worthy and what work is already going on in that area and what additional improvement would we bring about. After a successful defence, we move on to thinking of various solution alternatives. We look at prior art in both academia as well as industry.


In the simplest terms, a quant’s role is to ideate and execute models that “fairly” price financial instruments. The “fairly” part is the trickiest, and you get to see skillful people come up with great ideas. Working with smart and intellectually hungry people is enchanting. As a quant researcher, my work is pretty much financial research. I see people work, ask questions, try to answer some and learn tonnes every day. For analysis and implementation, a running knowledge of python and c++ comes handy. Reading research papers, thinking about ideas and discussions with my advisors along with the implementation of ideas form the major portion of my day.


The role of an SAP BASIS consultant is to provide technical support and leadership on SAP BASIS systems including establishing standards and requirements, implementing solutions for performance monitoring, and systems configuration, design and implementation. My assigned role was very basic and rudimentary- system monitoring. System monitoring is a daily routine activity and this document provides a systematic step by step procedure for Server Monitoring. It gives an overview of technical aspects and concepts for proactive system monitoring. This was not what I was expecting from my internship, and so was understood by my Manager, so he shifted me to Materials Management.


My work at GFK involves looking into Consumer purchase dataset and another dataset involving the internet searches made by the customer before buying the product, and to look for any relationship that can be defined between the two. Ultimately we aim to predict consumer behaviour and the influence made on the purchase by internet searches. The task involves the use of heavy feature engineering and NLP for identifying keywords in search strings so as to establish any meaningful comparison between searches, landing page from search results and final purchase.

We have tried to cover companies of different profiles in the article, and we hope that this compilation will give you some clarity while applying for internships henceforth.


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Chief Editors: Saman Siddiqui and Varun Sule
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