Campus Recruitment: How can YOU get hired?

Campus Recruitment is an obstacle that almost all Engineering students face at some point in their lives. As a final year Computer Science Student, when I came across a dataset titled Campus Recruitment on Kaggle, I was instantly drawn to it, in hopes of not only understanding the general trend in the industry but also of reassuring myself that I was not a lost cause. Although this dataset is from an MBA college, I think it can still be used to extract valuable information about how ones academic choices can impact their placements.

The dataset itself is rather small and contains parameters such as a student’s choice of the board for school education, their scores in 10th and 12th grade, whether or not they had prior work experience, etc. Out of the 215 students present in the dataset, 148 students have been placed.

In this blog post, I would like to share some of the key insights I gained during my analysis of this dataset and kick off a discussion about the implications of these observed trends. However, it is important to come to terms with the limited nature of this dataset and the fact that it is not representative of the full spectrum of students that take part in Campus Recruitment programs.

If you would like to check out how I applied the CRISP-DM process this dataset along with the code used to generate the plots in this post, you can check out my work on Github here or on Kaggle here.

Question 1 :

I find this question particularly interesting because the general trend that I have observed in new parents these days in India is their increasing preference to enrol their kids into the central board of education than others. This dataset allows us to investigate the following two questions:

  • Are central board students more likely to get placed than others?
  • Are these kids more likely to be offered a higher salary than others?
Placements by Board of Education

From the above graph, it might seem that those who took a combination of Central and Others between their 10th and 12th grades were less likely to get placed than those that took Central or Others consistently. However, looking at the number of samples in each of these groupings, we see that (Others, Central) and (Central, Others) have significantly fewer samples than the other two. For our analysis, we will focus on (Central, Central) and (Others, Others) and see if one has any noticeable advantages over the other.

Here, it seems that the choice of the board doesn’t seem to particularly increase one’s chances of getting placed but maybe it has a role to play in determining one’s salary? Let’s check!

Salary by Board of Education

These two groups seem to have about the same average salary. If the board did indeed matter, we would expect one group to have a noticeably higher mean than the other. In case of the number of placed themselves, the (others, others) group does seem to have slightly higher chances of placements but this could be attributed to the difference in sample counts.

Now that we have checked potential reasons for parents to choose Central over others, let us now analyse this from a student’s perspective. The general opinion is that Central board can be much harder than others (i.e state board). Does this mean that students have to work harder to get placed in one group than the other? Let us check.

It seems that among the placed students, those from Central Board scored less in the 10th grade than their counterparts. This could be an indication of how the examinations in the central board tend to be more difficult resulting in a lower average score. However, the opposite seems to be true in the case of the 12th grade. Maybe the more rigorous process the students faced in their secondary schooling better prepared them for their 12th?

You know what they say: “Some questions are better left for a different dataset.

Question 2

Growing up with Indian parents, I was always told throughout my school days that I should work hard and do well in my exams so that one day I would be able to get a good job. This led me to always try and score as highly as I could on my examinations. With this dataset, let us try to answer the age-old question: “Is there evidence to prove that scoring higher in your school days helps you get placed?”

Comparison of Scores Obtained by Placed vs Non-Placed students

Interesting! There does seem to be a visible trend here. Students who got Placed (orange) seem to have on an average, scored better in both their 10th and 12th than their Non Placed counterparts (blue). It could be the case that the scores were indeed helpful in impressing potential employers but on the other hand, it is also possible that those students that worked hard in their school days developed the right mindset to keep working and built other skills that increased their employability!

Question 3

In India, when we complete our 10th-grade education, we are met with arguably the most important crossroads our lives. What next: Science, Commerce or Arts? Unfortunately, during my 10th grade, I was faced with a number of health issues and I had to rely on my parents and relatives to choose my path for me while I recovered.

They insisted that I take up Science, citing reasons such as “There’s a lot of scope for students of science!” and “You’ll get job easily!”.

Looking back on my journey so far, I do not regret having taken up Science because eventually, Computer Science is where I found my calling. But I’m curious to see if students in one stream are more likely to get a job than some other. Is my relatives’ line of reasoning correct?

Arts does seem to be lagging behind in placements but then again it has significantly fewer samples than commerce and science. For our analysis, we will focus on only Science and Commerce, which from the looks of it, have near-identical placement rates.

Maybe one stream is more likely to be offered a higher salary?

Salary by Selected Stream in 12th

Hmm. Even though the mean salary does look quite similar, maybe the difference lies in the distribution of jobs? Maybe the reason my relatives tried to push Science as the “superior stream” was that there are more high paying jobs than others?

Salary Distribution by Selected Stream

Looks like both streams have about the same spread of salaries. There are some outliers in both cases and Science does seem to have an ever-so-slightly higher third quartile value. But not enough to make it significant.

Conclusion: My relatives are lunatics.

Question 4

We finally come to what I think might be the most relevant information to an employer. A student’s MBA specialization is closely tied to the kind of skills that a company would be looking for and consequently, the salary being offered. The next closest qualification of importance would be the student’s undergraduate degree. Let us look at how these two features affect the salaries being offered.

Salary by Degree type and Specialization

It seems as though the highest salaries that were offered were to students who pursued the Marketing & Finance specialisation after obtaining a UG degree in Commerce and Management. However, these are clearly major outliers. It seems than in general, Students with a Science and Technology UG degree pursuing Mkt&Fin specialization were more likely to get higher-paying jobs.

Question 5

The last question that I would like to answer is an important one. Do companies seem to discriminate between men and women when it comes to placements and salaries?

There does seem to be a general trend that men in this dataset have been paid higher than women. But we can also see that the dataset contains fewer samples of females than it does of males.

Regardless, I think this is slightly concerning that we see hints of such biases existing in today’s society and that the dataset creator might want to take this up with his college!

Conclusion

In this analysis, we explored a dataset containing campus recruitment data for students from an MBA college. Through our analysis, we found that:

  1. The board of school education doesn't matter when it comes to placements or even salaries.
  2. Placed students seem to have performed better in their 10th and 12th exams than Non-Placed Students
  3. The choice of a stream does not really matter when it comes to placements from an MBA perspective.
  4. Among the various specializations, students with a Sci&Tech UG degree and Mkt&Fin MBA specialization appear to have slightly higher salaries.
  5. The salaries for female students seem to be generally slightly lower than men.

We must understand that the results and observations made in this analysis need to be taken with a grain of salt. As I had mentioned earlier, the dataset is highly limited and as a result, heavily biased towards a small set of students from a single MBA college.

When it comes to getting hired, there are innumerable different factors that also play a big role such as industry requirements, the emerging technology, global trends, the students’ communication skills, personalities, mindset etc.

Therefore, I urge you to simply follow your heart, make your own choices and give your all towards achieving your goals. Regardless of what a dataset might indicate as being the best stream or best specialization, ultimately, the best job is the one that makes you happy!

Good luck!

I'm interested in Data Science, video games and art! I'm looking forward to travelling the world, eating food and writing about it.

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