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T5E’s Placement survey 2021-22 was conducted 28 December 2021 and 5 January 2022 to study the statistics of the Placement season of 2021-22. The survey witnessed a total of 326 responses across the entire graduating class (UG+PG). The respondents spanned across various degrees (albeit disproportional) and departments who appeared for the placement season. Close to 67% of the respondents were UG’s (B.Tech + DD) and the rest were PG’s (MSc+M.Tech+MBA+PhD+MS)
The survey focused on several aspects, such as Preparation, Opinion, Academics and Career, relevant to the placement statistics of respondents. The following charts showcase the general demographics of the survey across students of different degrees and branches.
Demographics:
Note: Do glance through the above charts to understand the demographics of the respondents of this survey. These charts are key to explanations regarding the results we got for several questions, which depend heavily on one’s department/degree. PG students are underrepresented as compared to UG and there exist higher numbers of respondents among departments like ME, EE, CS.
In this article, we explore the preparation aspect of this placement season.
Communication skills are often tested by the interviewers and sometimes become a crucial factor in judging a position. It is observed that the average rating by respondents of their communication skills stands at 4 out of 5.
Considering that many students find it hard to schedule their placement preparations, it is not surprising to see that around 75% of the respondents had started their preparation just before the placements. There are few respondents who were able to kick start their preparations a year before the start of the season. Interestingly, the respondents who started their preparation a year earlier had a median CTC of 22.25 LPA and the ones who started right before the season had a median CTC of 18.6 LPA.
85% of the respondents used online materials for preparation. Around 45% prepared through coursework, and around 33% used books.
The role of internships in placement preparations was rated highly, at 3.9 out of 5 on an average. Practical exposure and real time work experience enhance critical thinking and productivity and eases respondents out in the domains they prepare for. The question of the relationship between PoRs and placements, which is often debated, usually sees mixed answers from different quarters. It was no different in this survey, considering that the role PoRs was rated 3 out of 5 on an average. There is a small negative correlation between the role of PoRs and ML and coding skills, indicating that perhaps the respondents haven’t taken part in PoRs in order to manage the workload of enhancement of ML, coding skills.
Under preparations, the survey covered five major domains: Coding, Analytics, Consulting, Product management and Finance. Core sector was excluded, considering that it is diverse and changes drastically from branch to branch.
Coding
More than half the respondents prepared for coding and analytics profiles, indicating their popularity among students.
Coding skills are usually tested in the preliminary round and are required to get shortlisted for the further rounds. Interestingly, over 90% of the respondents rated their coding skills 3 out of 5.
There is a strong correlation between respondents’ coding skills and the CTC they were offered. Both the mean and median CTC increased with the rating, indicating that strong coding skills may lay the foundation for a better CTC.
On account of the importance of coding platforms in applying one’s coding knowledge, through competitive coding, projects, competitions that help to develop skills and familiarize coding tests on the same platforms, the survey asked the respondents which ones they used. Leetcode and Hackerrank were popular options chosen by 80-85% of the respondents.
When it comes to the programming languages, 92% of the respondents stated they know Python, 65% of the respondents know C++, and 52% know C. Matlab, SQL,HTML,JS, Java were well known to nearly half of the respondents. Being an easily codable language with wide applications, python was top of the list of many respondents’ technical skills.
Analytics
This section covers Data science, Business analysis, Machine learning, Deep learning, AI and Data analysis domains.
Machine learning skills are often required to pursue a career in AI/ML related fields. This includes predictive modelling in data science. On an average, respondents rated their ML skills 3.27 out of 5.
There exists a slight correlation between the ML skills and the CTC offered. The dip at 3, however, is due to the diversity of domains and their requirements – not every analyst requires ML skills for pursuing a career in the analytics sector. Regardless, ML skills can be helpful on the road towards an analytics career.
Over 85% of the respondents stated they know machine learning, and 72% stated they know data structures and Algorithms. Half of the respondents were familiar with SQL and Deep learning. Around 95% of the respondents were familiar with MS Excel, while only 25% were familiar with Tableau. A small 10% knew PowerBI and Apache spark.
On account of case study competitions driving analytical thinking, the survey asked the respondents about their stints with case study competitions. Of all students who prepared for the analytics profile, 80% stated that they have not taken part in any and barely 10% showed success in them.
On the other hand, 40% of the respondents stated that they have taken part in at least one ML/data science competition, while 7% had participated in more than 3 competitions related to data science and ML. Interestingly, a trend observed between competition participation and CTC. The median CTC of respondents who did not take part in any competition is 17 LPA, while it is 21.85 LPA for those who participated in at least one competition and 25.75 LPA for those who took part in at least 3 competitions have a CTC median of 25.75 LPA.
Consulting
Consulting is the third most selected profile and often has shades of analytics and finance, which increases the probability of students who prepared for profiles like analytics, finance, business management, etc being placed.
Considering that preparation for this profile involves extensive case prep sessions among students, the survey asked respondents about their case group size. Surprisingly 35% stated that they worked on them by themselves and 50% reported a group size of over 3.
Contrary to the assumption that case study competitions will be popular among students who prepare for the consulting profile, 55% of the respondents stated that they haven’t taken part in any case study competition, while 20% of the respondents stated that they had won at least one.
However, we find a correlation between participation in case study competitions and CTC offered. The median CTC of respondents who had won multiple case study competitions is 22 LPA, while it is 18.5 LPA for those who participated in at least one competition and 13.5 LPA for those who did not participate in any.
On an average, respondents rated their quantitative skills 3.9 out of 5, and 75% rated them over 4 out of 5. There is no observable correlation between quantitative skills and CTC offered, however.
Finance
Finance is considered one of the most important profiles in the non-core sector. Some students possess certifications in CFA (Chartered Finance Analyst), NCFM (NSE Academy Certification in Financial Markets), FRM (Financial Risk Manager), etc.
Most respondents stated that they have not participated in any case study competition, while 10% stated that they have won at least a competition. We find a mild correlation between participation in case study competitions and CTC offered. The median CTC of respondents who had won multiple case study competitions is 22LPA, while it is 18.5 LPA for those who participated in at least one competition and 16 LPA for those who did not participate in any.
Product Design and Management
A stable profile with decent placement offers, product development covers domains like product management, product design, Graphics designing.
Over 60% of the respondents were well familiar with AutoCAD and Canva. Since AutoCAD is used in core related coursework and Canva is often used in PoR work, these are softwares preferred by students prior to preparation. Adobe Illustrator, PhotoShop, After Effects, Figma were also used by a considerable number of respondents.
Conclusion
- Over half the respondents had prepared for either a coding or analytics profile.
- Around 75% of the respondents had started their preparation just before the placements.
- The respondents who started their preparation a year earlier had a median CTC of 22.25 LPA and the ones who started right before the season had a median CTC of 18.6 LPA.
- 85% of the respondents used online materials for preparation, while 45% used coursework.
- The role of internships in placement preparations was rated highly, at 3.9 out of 5 on an average.
- Leetcode and Hackerrank are popular choices among respondents, with 80-85% using them.
- The median CTC of respondents who did not take part in any data science/ML competition is 17 LPA, while it is 21.85 LPA for those who participated in at least one competition and 25.75 LPA for those who took part in at least 3 competitions have a CTC median of 25.75 LPA.
- 35% of those who prepared for a consulting profile had a case group size of 1, while 50% had a case group size over 3.
We received several generous tips by our anonymous respondents at several points in the survey. For the benefit of the student body, we have compiled them all here. We sincerely thank our respondents for their valuable insights from their placement journey.
