How To Build A Career In Data Analytics From Scratch

In conversation With Prateek Singla, Data Analyst At McKinsey & Company. He gives us an insight into a career in Data Analytics — the career routes and what is it like to be a Data Analyst.
Reading Time: 5 minutes

Prateek Singla works as a Data Analyst at McKinsey and Company. With a degree in Electrical, Electronics, and Communications from Vellore Institute of Technology, he has previously worked as a Business Technology Analyst at ZS Associates and Accenture.

Competencies: Excel, VBA, Tableau, Alteryx, Data Analytics, Machine Learning

The article is written to give insights into a career in Data Analytics, depict the career routes and to help the aspirants gain career clarity about a Data Analyst’s life.

Career Progression

What were the subjects you were interested in during the college days that have helped you as an analyst?

Prateek Singla: Programming and Mathematics. After being confident in these skills and to gain more clarity, I researched and published a paper on performance analysis of a communication system. It focused on the telecommunication sector for increasing performance.

What was the flow of the placement process in VIT? Where did you get placed?

Prateek Singla: We were asked to attend the training program and apply for all companies in the service sector and one core company. The training program aimed to make us well-equipped with the placement drive, helped us to prepare for aptitude tests and the interview process.

I got placed in four companies but decided to go with Accenture.

What was your job profile at Accenture?

Prateek Singla: I was on the Quality Assurance team. However, I wasn’t enjoying it much. I wanted to work with the analytics team and tried to figure out means to contribute to the analytics department too.

What did you do to grow in the analytics domain?

Prateek Singla: Analytics requires a deeper understanding of statistics and one needs to be well-equipped with Excel. These are the basic requirements, besides having a strong bent towards logical reasoning. Hence, I started to learn Excel, statistics, various tools like Tableau, Alteryx, and the basics of analytics through online certification courses.

In the meantime, I started looking out for opportunities where analytics would have been my core role. ZS Associates was one such company where I thought I’d be able to probe deeper into the field, and I wanted to be a part of it. A friend of mine, who was already an employee at ZS, referred me and passed my resume onto the team. I got an interview call with them. I had to clear a written exam, which focused on my aptitude level, followed by various rounds based on puzzles, guess-estimates, case studies. That is where my journey as a Data Analyst began. I started working in the Business Intelligence and Analytics domain and started honing my skills in data analysis.

How did the switch from ZS Associates to McKinsey happen?

Prateek Singla: Working in ZS was a big learning experience for me. I got to try my hands at core analytics and I liked it. I was not looking out for a switch aggressively, but I was lucky enough that opportunities knocked on my door. I always kept my Linkedin profile updated, and I got interview calls from Google, Goldman Sachs, and McKinsey. I cleared all three and decided to make a switch by accepting McKinsey’s offer.

Having said that, I’d say that the online certification courses which I did helped me secure these jobs.

Can you name a few courses you did?

Prateek Singla: Descriptive Statistics, Inferential Statistics, Predictive Analysis, Machine Learning, edX Honor Code Certificate for Data Analysis: Take it to the MAX().

What are the skills one is expected to be well-versed with during an interview?

Prateek Singla: One has to have an exceptional knowledge of the puzzles, case-studies, guesstimates, and really quick with calculations.

Can you cite a few examples of guesstimates that were asked during your interviews?

Prateek Singla: Recruiters generally provide you with a very limited information, and expect you to come up with the logic behind every guess, at every step. They would ask questions on every statement you would make, and your final answer should be accurate to at least 90%.

Once I was asked that if there are 1 million smartphones in Delhi-NCR, what is the population of Delhi-NCR?

Once I was asked to predict Gmail’s revenue in India.

Connect with Prateek Singla for Career Guidance here.

Resume & Interview Preparation

What are the essential points a fresher must mention in his CV for a Data Analyst’s role?

Prateek Singla: One should:

-Be able to mention a project he has undertaken during his college time, and produced results in the same.

-Highlight 4 factors in the project: Problem statement, Solution, Tools/Techniques Used and Error and Success Rate.

-Build his resume in the form of numbers, i.e., every statement should be supported by relevant metrics.

-Be able to visualize information or inferences in a creative manner.

Important things that a perfect resume should have are:

  • Job experience and job profile mentioned clearly. If it’s a resume of a fresher, it should start with education, knowledge of tools and/or programming languages
  • Skill sets and projects were undertaken
  • Maximum information in minimum words.

Can people from non-tech background learn programming languages used in analytics?

Prateek Singla: Yes. In fact, all that is required to have a sound knowledge is the logical reasoning. The languages are very basic and can be learnt in a week.

What is the general process of recruitment for on-campus hiring? How should one prepare for it?

Prateek Singla: The applicants are asked to send in their resumes. If the number of applicants is huge, short-listing is done on the basis of one’s resume otherwise it begins with a written aptitude test.

Written Round: One can prepare from the material what students generally preparing for CAT refer to. RD Sharma books for XI and XII standards help too.

Group Discussions: One is expected to be in the know about of all the current topics. Engagement in the discussions and clarity of thoughts help recruiters notice you.

Case Studies: All information related to demographic divisions, the classification and distribution of economic, social disparity, information on cities, the population of every state etc. should be learnt. It helps a lot in solving the case-studies quickly and accurately.

Pro Tip: Generally, case studies around the recent topics in the market are asked.

Technical Rounds: These rounds test you on what you have written in your resume. One should speak in numerical terms, and support every statement with numbers.

Guesstimates and Puzzles: These are the deciding rounds. The interview starts with questions related to puzzles or guesstimates revolving around one’s hometown, mode of communication, the nature of people, etc. One must know everything about his belongings.

Pro Tip: For puzzles, one can prepare by googling the recent puzzles.

HR Round: One should know about the company’s history and be aware of the job description. One should also mention his strengths and weaknesses clearly. Weaknesses should be highlighted in a positive way.

How should one go about for the off-campus placement or internships?

Prateek Singla: Keeping a check on the career sections on the dream companies’ websites is the best way to keep track of suitable openings.

These are the key factors one should keep in mind when applying for off-campus placement for a Data Analyst’s role:

Recruiting Time: DO NOT apply when the campus placements are going on.

LinkedIn Profile: Keep it professional and updated. Get in touch with the analysts working in the dream companies, and keep track of the openings.

Referrals: Referrals prove to be the most successful. Once you get an interview call, it’s upon your capabilities to crack that job.

Any career advice for the people aspiring to be in a similar role?

Prateek Singla: Data Analytics is something that one would enjoy only if he is passionate about numbers and has the creative ability to segregate data and make relevant inferences. So, before you decide that you want to make a career in this domain, be sure of it.

“This interview is a part of our Experts’ Insights series, where we try to gain an insider’s perspectives into different careers by engaging in dialogues with professionals successfully working in the respective fields”


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