Hey everyone! I am Bhuvan Aggarwal, a 4th-year student in the Civil Engineering Department. I am from Chandigarh and completed my summer internship at Daikin, Japan in the analytics profile.
The journey:
I had been working in the Deep learning field from my first year so the choice of target profile was a no-brainer. In particular, I wanted to experience corporate research in Deep learning which is highly profound in Japanese Companies so it narrowed down the search even further. But since these companies start coming around mid-August, I sat through some of the swe and analytics (majorly business analytics which I don’t like at all) interviews to get experience. Daikin came around the end of August and I really liked the work description. There were 2 rounds for selection, the first being the technical test and SoP submission. The test consisted of some coding questions and some regex-based MCQ type questions. But the SoP is the most important. Japanese companies really value their culture and like to hear about your liking towards it. If a Japanese company is asking for SoP then you can be almost certain that the shortlisting will be done based on the SoP and the test is just a facade. The structure of SoP was straightforward with the first question being on how well you are able to apply your ML-DL knowledge to a Daikin use case. The rest of the questions were basically to gauge the interest of students in their culture and how well they would be able to adapt to it. The second round was an interview of 15 mins. They asked a few things about the past projects and internships because some of them were along the lines of the projects which they had in mind for the interns. After that, they asked some HR questions too. Overall it was a fun and chill interview 😀
Preparation:
For analytics, the preparation basically involves resume prep like having a thorough knowledge of the previous projects and internships, basic ML prep (banks which come for pure analytics or more of business analytics type roles love to ask these). For ML prep, there are many websites where you can find ‘top 50/100 data science/ML questions for interviews’ and generally the questions are directly from these or a slight variation. If you don’t feel confident even after going through these websites then try going through the andrew ng notes which can be found here. Few companies like amex try to go into the maths of algos as well so that will also be covered in these notes. Then comes the DSA prep. For analytics, in particular, DSA is not that much required. The coding tests for analytics companies can be mostly solved by simple logic or as we call it the brute force approach but you never know, they might decide to put questions a level above. So, having basic DSA knowledge won’t hurt. Atleast go through the theory and try out some questions of important topics like graphs, trees and dynamic programming. But if you are targetting swe roles then you need to have good grip over DSA. One of the most popular combos for this is hackerrank+leetcode. Lastly there is the HR prep for the interview. So for the HR part there are some standard questions which you can find in the doc here.There are some traps in such questions which you would like to avoid. I would also suggest going through the company’s website before the interview and try to subtly add some pointers about their culture and values into your HR answers to show your alignment with the company. For Japanese companies in particular, try to show your interest in their culture while giving the HR answers and read about what all values/things they prefer in candidates like company loyalty, teamwork etc.
Internship experience:
Unfortunately, the internship was WFH because of the pandemic. So, I missed the opportunity of going to Japan. But overall the internship experience was quite nice. The work was based on image processing and we had to come up with solutions to solve an industry problem (Sorry, can’t divulge much because of the NDA :P). The people at Daikin were quite sweet and supportive and to ease out the communication they had allotted us mentors of Indian origin since not many Japanese people from tech industry are good in English. The internship was for 8 weeks with 2 evaluations based on a mid term presentation and a final presentation. The presentations had a live interpretor to translate english to japanese for the peeps from Daikin, which was quite irritating at times, but apart from that everything was nice. Coming to the WFH experience, I would say there are both pros and cons. The benefits are that you are sitting in the comfort of home and having good food. And one of the most important things is that the timings are flexible and apart from scheduled meetings you are free to work whenever you want which is obviously not the case with an in-office intern. The downsides are that I wasn’t able to visit Japan which I really wanted to and also the vibe and experience of the in-office intern is really different from WFH. In WFH you are just working and working but when you are in an office its completely different, you get to interact with lots of people, give offline presentations (believe me, its a great experience), obviously visit new places and much more. In particular, I didn’t face many problems with WFH since the mentors were very supportive and were constantly trying to promote interaction among the interns. Moreover, I had dedicated workspace at home so didn’t have much logistic issues while working from home. Overall, I would say the experience was quite nice and I got to learn lots of new things and developed my skills.
Tips:
I would say try to finalise the profile and start with resume and prep as early as possible. Dont try and apply to every company in every profile. Its wont do any good and will just waste your precious time. Even if you get an intern with high stipends or better benefits so to say but you dont like the profile or the work being done then it will turn out to be an absolute nightmare. So make sure to not deviate from your chosen path and rest everything will fall in place. Read the work descriptions carefully and dont fret over stipends etc.
Dont get anxiety or feel jealous by seeing others’ resumes or shortlist. Not getting a Day1 intern means nothing and is not at all necessary if you are targeting specific companies or profiles like analytics since not many analytics companies are there on day1. Dont lose interaction with friends or get disappointed over rejection. Remember to learn from failure rather than crying over it. Intern season will be very random and sometimes quite uncertain so give it your best and dont lose hope. It will be a new and interesting experience and you will do fine. All the best!!
