Placement Survey 2020-21: Academics

Design: Swati Sheenum, G Shreethiga, Shaurya Rawat, Abhiram Pavithran O, Rohit Gadarla and Hardhik Pinjala.

T5E’s Placement Survey 2020-21 was conducted in the month of February to study students perspective of placement season 2020-21. The respondents of the survey were final year students across different degrees and departments who appeared for the placement season of 2020-21. The survey witnessed a total of 171 responses from undergraduate students and 96 responses from postgraduate students. The survey explored various aspects like Opinion, Academics, Career, Extra-curriculars and Preparation in the view of placements and the effect they might have on placements.

In this article, we explore the Academics aspect. This article explores how various academic qualifications affect placements. The article is divided into two parts: Undergraduate and Post-graduate.


Branch wise distribution of respondents 

The survey had the majority of respondents coming from the Mechanical engineering department which was expected given the strength of the department. Next came EE, CH and CE, in that order. Departments that are not present in the above chart did not have a respondent for the survey.


12.9% of the students responded saying they belong to IDDD out of which the majority were from Data Science (47.6%) and robotics (33.3%).

Does being an IDDD student affect placements? 

Being in IDDD does seem to affect placements slightly. There was a slight positive correlation of about 0.32 between the slot you get placed and whether you are an IDDD student. Among the different IDDD fields, Data Science had the highest number of students getting placed on Day 1 with about 70% of students getting placed on Day-1 itself. Next came the Computational Engineering field with two students placed in the 1.2 slot. It was then followed by robotics and energy system. Also, all the respondents of the survey who are from IDDD-Data Science were placed before 2.2.

So yes, being in IDDD does increase your chances of getting placed in a better slot. This might be due to various reasons. As the CGPA cutoff for IDDD is high, the CGPA helps the students get placed in a better slot. Another reason could be, more opportunities for IDDD students on Day 1 and Day 2 due to companies opening up for their stream.


The majority of the students responded saying they did not do any minors. Among the various minors, AI/ML minor was the most popular one, closely followed by economics.

Minors overall seem to not have much effect on the slot a student gets placed in. The AI/ML minor does have a slight positive effect on the slot but it is not significant. Another reason to not have a conclusive answer about the effect of minors on the slot is the number of respondents who have done minors was very less making it difficult to conclude anything about their effect on the slot.

CGPA and Slot 

A majority of the respondents had CGPA in the range 8.0-8.5, followed by students in the range 8.5-9.0 and 7.5-8.0. The distribution was a slightly skewed bell curve which was pretty much expected.

Coming the distribution of slots students are placed in, 1.1 had the highest number of respondents! We can only guess that the reason for this is most of the UG students who took the survey were placed in 1.1 slot, followed by 2.1 slot. Another minor factor that might have affected this can be the no. of companies and offers made in each of the slots which was higher this time for the 1.1 slot as compared 1.2.

Coming to the million dollar question now,

Does CGPA affect the slot a student gets placed in?

Yes, Yes it does. CGPA had a correlation of 0.67 with the slot a student was placed in! Meaning, on average the higher your CGPA, the more likely it is that you will get placed in a better slot. The distribution of CGPA vs slot was as follows:

The average CGPA as is visible was 8.74 for students placed in 1.1, 8.28 for students placed in 1.2. This average reduced drastically from 2.1 to 2.2 with the new average CGPA in 2.2 being 7.6. As is also apparent from the graph, the average CGPA keeps on reducing as the slot of placement is increased.

This trend can be due to various reasons again. Companies having CG criteria for applicants, the general preparation level for core and other sectors might be higher for people with higher CGPAs etc.

Also, note that these are average CGPAs across the slot. There were cases where students having CGPAs in the range 7.0-8.0 were also placed on Day-1 and students having CGPAs higher CGPAs in the range 8.5 – 10.0 were not. These are overall trends and having a lesser or more CGPA does not guarantee a better slot.

Profile & Package  

Most of the UG junta was placed in Software Development and Core profile. Data Science/ Analytics profiles came third in popularity accounting for 18.8% of jobs.  Consulting, Product Management and Business Development also accounted for a considerable chunk of jobs.

One interesting trend here is the popularity of the non-core sector among UGs. The non-core profiles seem to be dominating with about 77.2% of the students getting placed in the non-core sector.

Coming to the “important” points now, the majority of students have their monthly base pay in the range 1L-1.25L which is about 12 LPA – 15 LPA in terms of base pay. This was followed by 50k-1L and 1.25L-1.5L. There were fewer respondents for base pay higher than 1.75L. There was also a group of students responding that their base salary is 3L+ per month which is 36LPA + in terms of base pay.

Base pay and slots were highly correlated as expected.


Branch wise distribution of respondents 

For PGs, the branch with the highest number of responses was CS, followed by EE and ME. Branch seems to affect placements for PGs, with the majority of the PG students placed on Day-1 and Day-2 honing from the CS and EE branches.

CGPA and Slot

Like the UGs, the majority of the PG respondents had CGPAs in the range of 8.0-8.5. One difference was the proportion of PG respondents having CGPA in the range 9.0-9.5 which was higher than UG respondents having CGPAs in that range.

Coming to placement slots, a majority of PG respondents claimed that they are not yet placed. Out of the ones placed, 1.2 slots accounted for the majority of those students. The proportion of unplaced PG respondents was higher than unplaced UG respondents.

Profile & Package 

The majority of the PG students claimed that they got placed in their respective core sectors. SDE and Data Science/Analytics also accounted for a major chunk of the jobs. Coming to the base pay, the majority of the respondents had base pay in the range 50k-1L per month translating to 6LPA-12LPA per month. The average pay for PGs was lesser than the average pay for UGs. However, the highest pay was still the same as a group of PG students bagging 3L+ monthly base packages.


Academics are obviously the most important aspect of insti life. After all, this is why we all are here for (well, most of us anyway). From the point of view of placements too, it does seem to play a significant role. Some of the key findings of the survey were:

  • CGPA on average has a positive effect on the slot you get placed in for both PGs and UGs.
  • Being in IDDD for UG Dual Degree students slightly improves your chances of getting placed in a better slot specifically if you are in the Data Science stream.
  • For PGs, the branch seems to affect the slot of placement with CS and EE students bagging offers in the higher slots.
  • The highest monthly base pay for both UGs and PGs was 3L+. However, the average base package was higher for UGs than PGs.
  • The proportion of unplaced PG students was higher than unplaced UG students.
  • A majority of UG respondents claimed that they got placed in the 1.1 slot!

That’s it from the Placement Survey this year! We hope that overall it was insightful and interesting for everyone!

Stay tuned for more analysis!

Write a Comment

Your email address will not be published. Required fields are marked *