The Smart Cube (TSC) Interview Questions for a full-time job as a Data Analyst by Namita Ahuja
Process – The whole process, divided into 4 stages, was conducted via online platforms. It was organized across the span of 5-6 days starting from the Pre-Placement Talk and ending with the HR-Business Round. Results were declared in a week’s time.
Interview Process
Round 1 (Aptitude Test)
- Questions were briefly related to basic statistics, data interpretation, logical reasoning, verbal ability and quantitative aptitude.
- The level of questions was easy, but speed was the matter as 70-80 questions had to be attempted in 90 minutes.
Second Round (Group Discussion)
Second round was Group Discussion. The topics for discussion were mostly relatable to the then scenarios and current affairs. It ranged from Lockdown’s Pros/Cons, Data breaching, OTT, Mental health, etc.
Round 3 (Technical and Logical)
This round was based upon Technical and Logical acumen.
Technical Round:
It started from introduction/resume overview, jumped to the projects worked on and then questions related to project as well as stats, ML and data analysis were asked. Candidates were inquired about – the accuracy metrics used in Regression/Classification, difference between R-square and Adjusted R-square, feature engineering, handling missing values, data collection, statistical tests, p-values, etc.
Logical Round:
It was to test the approach of candidates to solve real-life problems. Guesstimates and Puzzles were mainly asked. Puzzles were from Geeks for Geeks and guesstimates were mostly related to market sizing like how many tennis balls can fit inside Boeing 747, how many vehicles would you find on XYZ road, etc.
Round 4 (HR Interview)
Fourth and last round was HR-Business Round.
This round was again to check the logical prowess of the candidate. In this round general HR questions like why data science, where do you see yourself few years down the lane, why this company, expectations, etc. were asked.
Again, few guesstimates/puzzles were asking along with a data science case study. Example of one such case study: What factors do you think come handy while determining the fares in Delhi Metro? Another one was: Suppose there is a firm which wants to do certain product shuffling within the company so on which all factors one would decide whether to implement that plan or not?
Mostly features/factors affecting the target variable in the given case study were asked. Some questions related to ANOVA, Chi-square and other statistical tests were also asked.
Suggestions:
- Try not to fumble while communicating with the interviewer. Ask for time, frame answer and then speak wisely.
- Be honest. If you don’t know the answer to a particular question, then accept clearly that you don’t know about that topic and willing to learn it further.
- Always show team spirit via your gestures.
- Stay calm-composed throughout. Even if you are unable to give answer to all the questions asked then also don’t let pressure mount your head.
- Rather than blabbering in front of interviewer show that you are smart, and you think before speaking. Don’t let the interview feel that you have mugged up concepts.
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