By Ranjani Srinivasan and Abhinay Reddy
The 2012-13 academic year has now come to a close. The Placement Season began in December 2012 and went on well into the even semester. T5E presents a summarised report on the placement season along with some analysis of the trends.
T5E acknowledges the role of the placement team in providing us with all the data required; a special thanks to the Placement Office, and Karthik Abinav, Placement Web-Ops Coordinator, 2012-13. It is stressed that the article is only intended to analyze trends and it would be inappropriate to draw conclusions from individual data-points. In case of any discrepancies or problems about the statistics and choice of statistical representation, we encourage the readers’ cooperation by pointing out and enabling correction of the same.
Note: In several statistics below, foreign currencies have been converted to INR after accounting for their Purchasing Power Parity (PPP). Such conversions paint a more accurate picture of the true purchasing power of the money offered. In every case, it has been explicitly stated whether the conversions were done using PPP or without. In the latter case, the prevailing currency exchange rates were directly used to convert foreign amounts into INR.
- A total of 232 companies sought to take in students and a total of 63.6% students walked away with at least one offer in hand.
- 1282 students had registered for placements, of which 782 were placed in the season.
- Additionally, there were 33 pre-placement offers accepted by students.
- Multiple offers: 62 students had two offers, 28 had three offers, 3 had four offers and 5 had six offers made to them.
Companies and Sectors:
As usual, IIT-M was visited by companies from diverse sectors. As expected, a good fraction of job offers fall under the Core and IT sectors, with the rest filled up by non-core sectors and others:
The following is a plot of the maximum and minimum packages offered by sector. Please note that all foreign currencies have been corrected for PPP.
An interesting observation here is that there is no significant difference in the maximum pay offered across the IT, core, analytics and finance sectors.
The following graph presents offers in lakhs of rupees per annum by companies/institutions which recruited more than ten students this placement season. The salary offered by Land Transport Authority has been converted for PPP.
(The package that accompanies each company is indicative of the mean annual salary offered by the respective firm.)
CGPA vs Package Offered:
Always a crowd-favourite plot, this offers insights into the truth of the theory that academic performance directly reflects in the packages received. The graphs have been plotted programme-wise; the data points are presented in the table below. It should be noted that the salaries used in this graph have not been converted for PPP, and the values shown are averages.
The numbers in the table represent the average salary in lakhs of rupees per annum. It should be noted that the salary for 9-pointer B. Techs. is unusually high because of several students (especially from Computer Science and Engineering) who were recruited in offshore companies that pay high USD salaries, coupled with the fact that the total number of 9-pointers who sat for placements was not very high.
The numbers in the table have been represented in the graph below.
The department-wise and programme-wise average and highest salaries are tabulated below. Please note that these values are not PPP-converted:
Mean salaries tend to be heavily influenced by outliers, and are not indicative of general trends for small data sets. The median salary offers better perspective in these cases. A similar table with median salaries in presented below. Please note that in this table, foreign currencies have been converted using PPP conversions, which results in noticeably lower values as compared to the previous table. Once again, the salaries are in lakhs of rupees per annum.
The following plot captures the essence of the above tabulations, summing over all programmes in each department to yield a good idea of the department-wise distribution. All the salaries presented in the graph have been converted for PPP. Although the maximum salaries vary widely across branches, there is not too much variation in the median salaries; as usual, however, Computer Science and Engineering is an exception to this rule:
The following graph presents median distribution of salaries in lakhs per annum by programme. The salaries used to obtain these numbers were not converted for PPP.
The figures for B. Tech and Dual Degree are more indicative of actual figures than MSc or PhD, because there are far fewer students in the latter two programmes.
The following table shows the percentage of students placed, department-wise. Please note that these percentages are with respect to the number of students who registered for placements (and does not include those with other career plans):
The following plot brings out the same statistic by programme:
In keeping with the trends of last year, the highest percentage placed was in the MBA programme, followed by B. Tech and Dual Degree.