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How to kickstart a career in Data Science

What does a Data Scientist do? How can you get into the Data Science field as a fresher and with experience? What are the qualifications and requirements to start a career in Data Science and Analytics? Sayan Putatunda covers all these questions in this article.

How to kickstart a career in Data Science?

By Sayan Putatunda

Sayan PutatundaData Science is the latest buzzword in the industry. Even though initially many dismissed it as a mere fad but now over the years various organizations have realized the potential of data science to generate actionable insights from structured and unstructured data.

From banks to ecommerce firms to even manufacturing industries, all of them have understood the importance of data science and have adopted it in their day to day business activities to improve their performance.

The role of a data scientist has already earned the moniker of  “the sexiest job of the 21st century” [1]. According to a report by the Mckinsey Global Institute [2], there will be a shortage of 140,000 to 190,000 data science professionals by 2018 in USA alone.

As far as India is concerned, there are some studies that believe that the Analytics/ Data Science industry in India is at a phase where IT was some 10-15 years ago and thus a boom can be expected in analytics outsourcing to India [3]. 

I also believe that India with its data science/ analytics talent pool can very well be the leader in this industry. Already there are some success stories such as Mu Sigma and Fractal analytics. Moreover, we are now officially living in the age of the “Big Data”.

So it`s quite clear that why the data scientists are in demand and also a lot of new jobs would be created in this field in the near future. Hence, data science can be seen as a lucrative career option.

What does a Data Scientist do?

Data Science is an amalgamation of proper business understanding, mathematics, statistics, programming and communication skills. Thus one is expected to display all the above-mentioned skills in the role of a data scientist.

It is expected that a data scientist understands the business problem, builds a hypothesis, understands the kind of data required, performs data cleaning and preliminary data analysis, builds statistical models to give solution and finally effectively communicate the insights to the client. Thus, the job of a data scientist encompasses various roles and functions.

Getting into Data Science as a fresher and with experience

Now to ensure that your resume grabs eyeballs when you apply to an analytics firm needs some preparation. The preparation would be different for a fresher than for someone who already has some work experience under his belt albeit in a different domain.

For a fresher generally engineering or maths/ stats graduates the focus is more on analytical problem solving and exposure to some programming language. And then they can apply to analytics firms either through campus placements or  off-campus placement drives and try to ace their interview process.

But for someone with substantial work experience in some other domain say an IT professional, it`s a different story altogether. An IT professional is generally good at programming skills but they fall short by quite some distance when it comes to mathematical intuition or depth in business understanding.

So for an IT professional or in fact professional from any other sector, it`s a bit difficult to make transition into Data science but not impossible. I have successfully made this transition and hence can vouch for this fact.


How to start a career in Data Science and Analytics

Analytics or Data Science recruiters are on a lookout for relevant skills and so the trick is to acquire these skills over a period of time & leverage them during an interview. Now let`s discuss the various aspects one needs to work on to make a successful transition to the analytics industry.


1. Get a Masters (MS / MBA) degree with business analytics specialization

This is obviously the traditional route i.e. start with a clean slate. One can enroll themselves into a postgraduate programme in analytics.

For example – IIM Calcutta has started a PGP in business analytics with ISI Kolkata and IIT Kharagpur a couple of years back and this programme is doing well.

There are some very good masters programmes in various US universities as well. For example, North Carolina State University, MIT Sloan, UC Berkeley, Texas A&M, etc.

One can even go for a general MBA degree but take some analytics related electives such as advance data analysis, machine learning, etc.
But then this is something that might not be possible for everyone for various reasons. In that case, one needs to focus on self-learning and effective utilization of freely available learning resources at their disposal. Some of these are discussed below.

2. Build Statistics / Machine learning foundations

It is expected that an aspiring data scientist should have some familiarity with various statistics or machine learning methodologies used in the industry.

One can start from the basics i.e. normal distribution, central limit theorem, hypothesis testing and then move on to advanced techniques viz. linear regression, logistics regression, decision trees, cluster analysis, generalized additive models, etc.

A recommended book for this would be The elements of statistical learning (by Hastie, Tibshirani and Friedman).

Apart from the standard textbooks, an alternative but effective way of learning would be going for MOOCs. There are a lot of free statistics/ data mining courses available via Coursera, edX, MIT open, Stanford online, NPTEL, etc.

3. Gain Technical Skills in Analytics

As far as the tools in analytics industry is concerned, SAS and SPSS used to be popular before the open source revolution took the industry by storm. Open source tools like R and Python are the next big thing and it would make sense to invest time on them.

There are enough freely available resources on the web to learn both R and Python. For people with coding skills in object oriented languages like Java will find Python intuitive. But R is the best tool (personal opinion) when it comes to statistical modeling and it is also the preferred tool in academia.

For an absolute beginner, the introductory course in R at can be a starting point. But the best way to learn these softwares is by doing. So I would suggest that one should replicate the codes available and test it on some dummy datasets to understand what`s going on.

Also, a working knowledge of SQL along with advanced MS Excel / VBA skills can act as a differentiator when one appears for their interview.

4. Read up on business applications of Data Science

Since data science is not only about technical mumbo jumbo so it would be really be helpful if one understands the business applications of it and one is also aware of various successful use cases.

This will help one see the bigger picture and also make one well equipped to understand what kind of methodology fits for a particular business problem.

For example, how market basket analysis is used for product bundling by retailers, how cluster analysis can be used for customer segmentation for a new product launch, how logistic regression can be used for fraud detection in banking/ insurance sector, etc.

5. Participate in various data science competitions

The last but not the least would be – practice, practice and practice. One way to do it would be by participating in various data science competitions hosted in sites like Even hosts data science competitions.

But I would suggest to go through some of the past competitions at kaggle and replicate some of the scripts to understand the modus-operandi. The level of competitions at kaggle is high and one can learn how to handle challenging datasets and come up with a solutions.

Also, the discussion on the forums with like-minded data science enthusiasts can be helpful.

Finally, even after one has got a break in the data science industry, one needs to guard against complacency. The way technology is progressing and the analytics field is developing, there is something new to learn everyday!
Related post:
Best online courses in data science
[1]         Thoma H. Davenport and D.J. Patil, “Data Scientist: The Sexiest Job of the 21st Century,” 2012. [Online]. Available:

[2]         James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh and Angela Hung Byers, “Big data: The next frontier for innovation,competition, and productivity,” 2011. [Online]. Available:

[3]         Bhasker Gupta, “Analytics Outsourcing to India: Should or Shouldn’t,” 2015. [Online]. Available:

About the author: Sayan Putatunda is currently a doctoral student at the Indian Institute of Management, Ahmedabad (IIMA) who is passionate about Data Science and Machine Learning. He is also a national level Powerlifter, a Marathon runner and an avid Reader.

Also read:
Data analytics for Automotive Industry

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22 thoughts on “How to kickstart a career in Data Science”

  1. Hi,

    Great Article !!
    I need help here. With my profile as working for an IT firm, I was mainly involved in work with Business Intelligence reporting tool MicroStrategy and SQL. Now, I am looking for change in profile and want to start my career in Data Analytics sector. Not having expertise in this is the major drawback for me and in a consulting company where I work, it’s difficult (not possible) to get a project having Data Analytics. Please suggest me which companies should I apply for changing my profile to Data Analytics without any prior experience. I have been working in a consulting firm for over 2 years now.

    • Hi Richa,

      Your SQL skills will come handy. I would suggest you target startup or boutique analytics consulting firms and try to get some analytics project experience there. You can also complement it with some certifications in analytics at some decent institutes. This will ensure a full transition into a career in analytics.

      • hi Richa,
        since you don’t have any experience in data analytics your chances of getting a good job are a little low.. you can go for certifications from simplilearn or data science council of america, these will definitely help you with your career.

  2. Hi Sayan,

    I graduated in maths 15 yrs back. And couldn’t take up a career. Now i have all my life to start a career. But i still wonder where to start and have a great fear if i would be even considered for a job having a tough competition by the young generation these days. I read your article its quite interesting. Is there any possibility for me to start a career in this field.

  3. Hello Sayan,
    I am a B.Tech Computer Science graduate and Performance tester from past 3 years with more than 7 years of testing experience. I started my career as a Mainframe developer and moved to testing, have very less experience in coding.
    I am interested in Data Science and planning to change my career, please suggest.

  4. Hi Sayan

    I work in an advertising agency and I feel I am dragging myself into an Account Manager role. I am looking for a grand switch into Data Analytics and subsequently further where it takes. Scavenging so many online resources on it, it seems extremely tough even after gaining hands on learning through MOOCs etc. I mean what next after that? How to begin? From where to begin?
    I did my PG Diploma in Marketing Communication with Hons. in Economics as major and Statistics as minor. I have a proven curiosity in programming ( certification in programming languages like C & PHP), but never built more on that.
    If i am running into fear, what could be the possible reasons?
    Is it because the Domain Switch Or Unproven expertise/Naive into this field Or Other reasons like redefining my long term goals?

    Pl. enlighten more on this career move towards the world of Data Analytics.

  5. Hi,
    Nice article more informative
    I need some help here, I’m a graduate in business management (BBM) I’m interested in data analytics. I’m a fresher looking for some courses related to it but confused what to do furthur got through this article and got to know it’s bit difficult for management based students.
    So please suggest me what to do. Shall I go for pg specialisation in data analytics or master’s in it ?? Or choose any other courses ?

    Thank you

  6. Hey there,
    I am an undergrad in Comp. Science (B.E.) currently. Data science (especially machine learning) intrigues me and I want a career in it. Please give me a suitable path to follow. (Mostly I won’t be able to pursue a Masters course due to financial reasons so I have to do it on my own.)

  7. Hi Sayan,
    Thanks a lot for this useful article, what exactly i was looking for. I am having 6 years experience in Web Development( Programming ) using C# language and sql server DB. Now ,I want to start my career in Data Scientist/Analytics . So , Please suggest me on this. It’s very very urgent..

  8. Hello Sir,

    I have 2.7yr of experience in manual testing in BFSI domain.I unfortunately have a year gap in my career after my work ex of 2.7yr.I do not have any coding experience and i am not good at it too.I have done course in ETL OR DATAWARE HOUSE testing.While during the course i developed the curiosity towards big data /data science.I have interest to move into data science field and yeah i want to start in the traditional way.I am planning to join the program offered by AEGIS SCHOOL OF DATA SCIENCE as their program is in collaboration with IBM.Also they have an oncampus IBM analytics lab and curriculam is quite comprehensive.I also feel certification offered here is also worth.
    I need your suggestion here ,the fees of the program is 6lacs for an year.Do you have any inputs regarding the worth of the program offered by Aegis school?Any other suggestions are also welcome.

    Pleas help!

    • Data Science is a combination of mathematics, statistics, computer science, business knowledge. Please evaluate where do you stand in mathematics and statistics knowledge from school and college level. Normally what I have seen is that around 80% + level of marks are needed in mathematical sciences in school and college level. A very good knowledge in business functions is also required.

  9. Hi am Siddharth,
    I am willing to start a career in data analytics so am thinking to do masters in USA/Canada
    So please suggest me because am a fresher with just 5 months experience. Does it worthy for me to do masters in data analytics.????
    Please answer me
    Thank You

  10. I am a fresher .B.Tech 2016 in Electronics and Instrumentation with no relevant work experience. I want my career in Dta Analyst/scientist.Have basic knowledge of JAVA and C, learning Python online.Please tell how to start career in thid=s domain because as a fresher people don’t hire neither there are any vacancy in this domain for fresher.
    What would be the best step taken by a fresher..please help..

  11. Hi
    I am currently working as a MS Azure cloud administrator. I would like to know about the colleges/ universities offering distance MBA in Business Analytics.


  12. Hi,

    I have done BE Instrumentation & have 6 years of experience in the field of Instrumentation.
    Now i want to have my career in Data science.
    I am good in mathematics & have basic knowledge of JAVA & Python.
    Please tell how to start career in this as a fresher.

    Can you please help me out with some universities where i can do this course.

  13. Hi…
    I m a fresher BSC.(hons) instrumentation with no relevant work experience .I just want to know is I m also eligible for this course. I studied maths as an generic subject .I want my career in data please tell me if I m eligible then how to start a career in this field.

  14. Hi..
    I’m a fresher BPH(Public Health) with no relevant experience of work and I’m interested in this field and i’m not a student of mathematics .So can you tell me that i am eligible for the course?

  15. What can be the expected return of investment on an MS degree from US (Georgetown University, DC & George Washington University , DC ) if one takes up a loan?


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