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“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” – Geoffrey Moore

Analytics, from a business perspective, holds significant stature in terms of making and breaking the company. It provides a basis for companies to describe, predict, and improve business performance and lay out their future plans. Basically the job entails creating a bridge between the data and effective decision making. Analytics is a booming industry today and the opportunities present are endless. 

We tried to talk with alumni working as analysts in four different companies and combined their excerpts to decode the experience and nature of job in analytics. Among the alumni, Amit Nagar is working as an analyst in CitiBank, Utkarsh is an associate in Capital One Datalabs, Deependra is a software development engineer in Amazon UK and Zaher is a senior Data Scientist in NoBroker.

Thoughts and options before choosing career paths

Like every field, analytics and the world beyond, is a farsighted island with little clue of opportunities and obstacles on it. Like every sailor, everyone carries a lot of options before leaving the shore of comfort and going on to the vast ocean of future opportunities. 

Amit Nagar working as an analyst in Citibank was a core/tech enthusiast and thought of going for higher studies or a startup but lack of good ideas and inadequate grades led him to try for a non-core job. 

Utkarsh, an analyst at Capital One Datalabs had also wanted to go for higher studies but he wished to take a break from the studies after getting a view of research life in college. Deependra is a software development engineer in Amazon UK and he wanted to launch a startup; inspired from many of our successful alumni like ( 

While Zaher, a senior Data Scientist from NoBroker was well aware of where he wanted to go because of the interest; he had developed towards data science. His interested was driven by his intern projects of data visualization where he saw an opportunity in data analytics. After which he started reading various entrepreneur blogs and figured out that the data based products and industries are going to grow and create a huge demand across India. 

Work culture & responsibilities:

Analytics is a work of collaboration between teammates, so their daily activities involves a great amount of interaction with their coworkers. In NoBroker, they start with a SCRUM. “A SCRUM is a meeting where the team tells you what the current status of their project is and what their plans are for the work For example, we are trying to build a Chat Bot, where one of the teammates is working in conversation modelling and the other one on intent classification. Both of them tell about their status and resolve dependencies to work for the future plan (Zaher, NoBroker)”

“The office has multiple Product Pods – small teams of around 6 members who collaborate to work on a product. Each Pod works independently on a product. I usually go to work at 12 PM and we conduct a 15 minute Pod stand-up where every team member discusses their completed work, planned work and any challenges that they encountered. On a typical day, I attend a couple of meetings for diverse purposes ranging from presentations to fun events like family feud. Our work environment is of a collaborative nature and it’s quite common to frequently call short team meetings to discuss problems. Lunch and evening snacks are provided by the office. After winding up the day’s work, I usually head home at 8 PM. (Utkarsh, Capital One Datalabs)

The responsibilities closely relates with meeting targets within the deadline along with the collaborative efforts of the teammates. But as you grow with the company, you are assigned to more leadership intensive tasks and are given a responsibility to manage a team, guide them and deliver targets.

Earlier I was more into building platform and products, than more of kind of typical data science job. Now as the company has grown. I have managerial responsibilities as well. Where I have to manage multiple projects and then I have to serve as an interface with the technology team and the data scientists. Our technology team is not very well aware of the ML or algorithm that go behind them. So they just know the implication of the product. They communicate the problems with us and I coordinate with the team to give solutions. For example, they told us we want to understand the sentiments of the customer when they chat with us. Now the product team tells me we need to implement the sentiment analysis model. That is the problem we are given. What I do is, I divide the work and allocate some people to pull out the data and others to create some models out of it, so I basically act as an interface between the technology team and the data scientists.(Zaher, NoBroker)”


There are many options to grow in a particular field of analytics. After getting an experience with working in a team of small people, companies often gives flexibility to adopt both technical and managerial roles.

There are ample opportunities to grow into different kinds of roles. While my daily work mostly consisted of technical work, I could still choose a path where I would grow into a business analyst role or even a managerial role such as a product manager. Of course every opportunity comes with its own set of challenges but given how open and diverse the employee group at this particular center is, there is always someone available to direct you in the right direction for pretty much everything (Amit, Citibank).”

Amazon works at a large scale, so in the company there are always bigger problems to be solved. You can always ask for more responsibility and learn from seniors. Since the company is working in multiple areas, it is easy to switch teams to work on different problem space (Deependra, Amazon UK)”

“I’m a key member of the team because I joined the team at a very nascent stage, and currently have a significant amount of stock and shares in the company. so, I’m growing with the company as well and learned as a data analyst, promoted to data scientist and now I’m a senior data scientist. It was a company of 80 members when I joined it and we worked in a small section of building at that time and now we have a 3 floor office with 1100 people. So the company is growing and I’m also growing with the company.(Zaher, No Broker)

Overall satisfaction

Software Engineering gives a lot of flexibility to express yourself with your creativity. There is so much impact of whatever you do which is only going to grow further in the future. There are options for work from home as well since all you need is a laptop. There is going to be lack of software/ML engineers for at least the next 10-15 years before automation  starts taking over all the jobs. It’s also very satisfying because whenever I get bored of one project, I can easily switch teams to work on a different problem.(Deependra, Amazon UK)”

I get very excited whenever a new project comes up. I wanted to work in a startup. We have all kinds of data like data in text, audio, image, geographical data points and other kinds of data. There’s a lot of data sitting in our cities and localities which is an actual inventory sitting out there and we just have to illustrate their use. It’s not some hypothetical service but a scope of interesting applications from which we can create lots of products.(Zaher, NoBroker)”

Expectations from the job prior to placements:

Expectations from jobs are like Goa trips, it doesn’t always happen as people plan it. End of the college life is an end of comfort, long night chit bits, movie marathons, hanging out with friends being lukkhas around the campus. So the dream of assuming a life as chilling as in campus may shatter into a thousand pieces. Talking to alumni working in your dream jobs or areas of interest is a great idea to get acquainted with work culture. But then, analytics is a stream that has many tributaries and people have found many cliches around it.

My expectation from the job was of flexible hours, meritocratic work culture where I could get my hands dirty with new technologies while learning about the markets. What I had heard from earlier interns and Alums working here is that it is not so exciting to work in an established fin-tech place as things get stagnant after a bit but I would disagree with that. My day-to-day role here is that of a backend developer but my managers here are very accommodating for my requests to explore things which has led me to explore UI, Blockchain, NLP, Big Data and more exciting fields. A recent addition to that list, this August I will be participating in a Hackathon working on ML classification and prediction project on real time market data. Although there are times when things are not so exciting and I had to sit till midnight on a weekend to solve random bugs in old codes but that is seldom. Being an Alumni of a premier institute, the management puts CAP Analysts on the most challenging tasks of the work which makes my work more exciting then the most people working at this place and It has turned out to be a good experience till now. (Amit, Citibank)”

After graduation, I thought I would be a superstar when I joined the company by making big changes. Soon I realised I know so little about how to write production level, bug-free, tested, readable and scalable code. There are a lot of thinking processes that you start using as you gain more experience. It took me time to ramp up before I start contributing. I am still not at the point of being a superstar, there are still a lot of things I want to learn.(Deependra, Amazon UK)”

Exit Options:

The major and usually the most preferred exit option at hand is higher studies. A lot of the people currently working in data analytics have listed further studies as the number one reason for leaving their jobs. 

I am looking for a role where I can put to use my core knowledge of Aerospace and Controls as well as my technical expertise. As Citi is not yet into that business ( and has no future plans that I know of), I am planning to go for higher studies and move into a role which suits my appetite best. While data science as a field is quite appealing, people do get disillusioned within a span of a few years (Amit, Citibank)

Words of wisdom

“The atmosphere in the campus during the placements is driven by glamour. Depression is natural and occurs in many areas of life where a large number of people are competing for few highly prized opportunities. I think it would help each of us to internalize that placements are beginning of a career and not an end in itself. Regardless of where you find yourself after your placements, I am confident that mentorship and hard work can help every student achieve their career goals. (Utkarsh, Capital One Datalabs)

“When you are in university, you always have your friends around you. You are playing games, preparing on last day for quiz or just chatting about nothing i.e. lukkha. All of a sudden your life changes when you start working 10-6, it changes even more drastically when you move to a city abroad where you don’t know anyone. I started spending time cooking, learning guitar (which didn’t work), visiting museums, clubbing, taking dance classes, gym etc. These activities keep me busy, helps me meet new people and grow as a person.(Deependra, Amazon UK)