Internship Experience | Divyansh Saxena | Teach For India | Data Science

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A. Direct one-to-one chat and Q & A with me for 20 minutes  [Cost: 1 “Felt”]

B. Guide to get internships (International and National) – I will help you in applying for internships in India and             outside India which have more chances based on your profile. [Cost: 3 “Felts”]

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Note: In case you (reader) is not satisfied by the service, the entire money would be refunded within 48 hours. No questions asked.   – Team InternFeel


I have worked for 8 other organizations before this one, since first year of my engineering. Major ones are with UC Berkeley, Tata Consultancy Services, De La Salle University (Philippines), Adapty.

IF: Please tell us something about yourself. What are your hobbies, interests. Where are you studying currently?

Divyansh Saxena (DS): I am Divyansh Saxena, currently pursuing BE in Computer Engineering (Final Year) from University of Mumbai. I am passionate about data science and entrepreneurship. I launched my first startup (notemybook) at 18 and within 1 year, got featured by Hindustan Times as Top under -19 CEOs and by Yourstory as Top 9 college start-ups that turned into big companies. From past 6 months, I have been working with California based entrepreneurs to launch a startup (Kernl, Inc.) in India and will pursue it further, after I graduate in May 2016. My hobby is to read non-fictional books mainly focused on entrepreneurship and leadership.Screenshot_2016-01-17-10-30-21-2

IF: Which internship did you get the chance to take? What was it all about? Stipend, duration and place?

DS: I interned at Teach For India as a Data Scientist from November 2015 to December 2015. My role was to increase the efficiency of organization by using Machine Learning. All in all, I had to implement various machine learning algorithms on different data sets. My internship was majorly divided into 2 projects. One was focused onto reduce the number of competencies that are involved in a selection of a fellow. Used different techniques like Regression, Clustering and PCA for the same. My second project was to build a prediction model that could automatically evaluate the essays written by applicants for fellowship using past data. Used Classification algorithms like Naïve Bayes and K-Nearest Neighbour for this project and built a model that could save 2400+ hours for the organization, hence increasing its efficiency. I was very much comfortable with R programming language and thus used it for these projects.

Stipend – Rs 4000/month

Duration – 2 months

Place – Mumbai

IF: How did you come to know about the internship? To what all sources you kept yourself connected?

DS: I came to know about this opportunity via Internshala. When I read its description, they had mentioned explicitly about their preference to Masters/PhD candidates but based on my past experience and skill set, I gave it a shot which eventually worked out for me. From first year of engineering, I have completed 9 internships at various organizations including UC Berkeley (USA), Tata Consultancy Services (India), De La Salle University (Philippines) Faadooengineers (India), Teach For India (India) etc.

Most of these opportunities were posted on websites like Glassdoor, Linkedin and Internshala and right from my first semester of engineering, I have been following them.

IF: Tell us about the procedure to apply for the internship. Who all are eligible to apply for this internship?

DS: Internshala, redirected me to Teach For India’s website where they had mentioned to email them, my resume and a cover letter. I got a response within 7 days and cleared this hurdle. Next was a telephonic interview which mainly circled around my past experiences. I won’t say this was completely a technical interview. After passing this round, I was called for an interview at their office. This round had 3 sub rounds. Starting off with a 15-min HR round which was mainly about my knowledge about Teach For India and my availability for the internship. Second sub round was a 40-min Tech Interview which was very interesting as well as a bit exhausting. The first 10-min was about my background and stuff. The interviewer had done his Masters from Columbia University in Statistics and he kept on firing statistical questions for next 30 minutes. I would guess that I had answered 90% of them correctly. Third sub round was a non-technical one. They had given me an article from New York Times and I had to write a for or against essay on it. I was given 40 minutes for it. After 15 days, I received a mail that I got selected for this internship role.

Candidates with Statistical knowledge and Machine Learning experience are eligible for it.

IF: Any common mistakes which you feel students should avoid while searching and applying for internships?

DS: I would like to share two lessons that I learnt from my experiences.

First – Students should have clarity about their interests and should pursue internships in those fields only. I feel lot of students make mistake here. Without digging up their interests, they pursue internships which are most of the times beyond their interest scopes and thus they end up performing adversely. My advice here would be to explore lot of domains as soon as you join your undergraduate school. In my case, during and after my first year, I started interning at different organizations and explored robotics, hacking, marketing, NGOs. But none of them made me interested in then until my second year, when I explored Analytics and found it exciting. Thereafter, I have pursued analytics and interned for TCS (Mumbai), UC Berkeley (California), Teach For India (Mumbai), Measurence (NewYork), Adapty (Mumbai) etc. So, key here is to start early.

Second – I feel lot of students go for brand of the company rather than project details while choosing an internship. Among good project or good brand, go for the former one. This will not only help you build relevant skill sets but will also eventually help you in getting a good job or getting a good admit for MS. Building profile is a marathon rather than a 100m sprint. You should start off with small companies, build skills and then shoot for big brands. This is a sure shot mantra for getting internships and building a great profile. In my case, I started of interning at ThinkLabs SINE IIT Bombay, Faadooengineers, De La Salle University (Philippines), Adapty, Measurence and gained some professional experience and then eventually landed up with big brands like TCS, UC Berkeley, Teach For India etc. So again, key is to plan and start early.

IF: Let’s talk about how competitive the selection process is. What qualities of yours, you believe helped you in having an edge in the selection process? What key things you feel were looked for by the selectors?

DS: This internship required in-depth knowledge about Statistics and Machine Learning. I guess having that gave me an edge in the selection process despite their preference to Master’s and PhD candidates. Apart from this, my communication skills helped me clear few rounds. Selectors were mainly looking for two things, one, ability to implement machine learning algorithms and two, ability to communicate results with the team.

IF: What preparations did you do after the results in view of the internship?

DS: I had less than a week in between the result and day 1 of my internship. Hence, I decided to brush up my R programming skills and looked up my previous work in R. Also, I was aware that this would require Machine Learning, I decided to revise theoretical concepts of few of the important Machine Learning algorithms which definitely helped me during my tenure.

IF: Could you please highlight the work/research project you carried out during the internship period? Its application in the near future and your work in it?

DS: I did two projects during my internship. I was the only one to implement these projects right from scratch. But, my manager had done his Master’s in Statistics from Columbia University and had great knowledge about this domain. So, whenever I got stuck somewhere, he used to pull me out of it with ease.

First – Reduce number of selection competencies used for selecting applicants for fellowship using Machine Learning. Used various regression models to test the significance of the parameters using p-value. Also, implemented parameter reduction techniques like PCA on the given data set to come up with selection parameters that directly impact the effectiveness of the organization.

Second – Build a prediction model that could automatically evaluate essays by applicants for fellowship and predict the result for each candidate. Used classification algorithms like Naïve Bayes and K-Nearest Neighbor to build this model that could save 2400+ hours invested by the organization in evaluating the essays.

These algorithms have many applications in real world right from Google Search, Spam/Non-Spam, Computer Vision etc. According to Prof. Andrew Ng of Stanford University, proper usage of these algorithms  have helped tons of Silicon Valley startups to earn millions of dollars and build great products and solve great problems.  

IF: What was the best thing about the work culture and the internship? What were the things you liked there?

DS: In most of the internships, your project is either a pilot one or something that is reviewed again and again by the supervisors before implementing it live. But, this internship was quite different. I was given lot of responsibility as an intern. The projects that I worked on were directly used by the organization to improve its effectiveness. This particular thing made me do the projects with lot more accuracy and sincerity along with freedom which I guess every intern love to have. Other thing that I liked was the office space.

IF: Let’s now talk about some negatives. What were the glitches and problems that came your way, which you think your juniors would be able to avoid?

DS: Despite a great office space, there were no arrangements for interns in my particular department as such. So there were times when I had to sit and work from other department which sometimes can be a problem if the project involves a large team. In my case, as I was solely responsible for the projects, I didn’t face any problem with the relocation. Apart from this, everything else was perfect.

IF: Was this your first internship / training? If no, please describe a bit of your previous internship/academic experience.

DS: No, this was not my first internship. I have worked for 8 other organizations before this one, since first year of my engineering. Major ones are with UC Berkeley, Tata Consultancy Services, De La Salle University (Philippines), Adapty. At UC Berkeley, I had done two projects, one was focused on data analytics using R. Here, I had to web scrape disaster data from 1850 to 2010 and perform descriptive and predictive analytics using R. Second project was to visualize Saturn Rings using Java and find patterns in gaps between it. At TCS, my role was again of a Data Analyst, where I was given employee data of past 4 years and my task was to find key insights. I used SAS, Excel for the same. Recently, I did my internship under Adapty. There I built an end-to-end analytics software for US based ecommerce clients which enabled them to upload customer data onto a server and see insights of it on an app. In the process, I learnt Talend (ETL Tool), mongoDB (NoSQL) and Microstrategy (BI Tool). I loved worked for Adapty despite of them not being a huge brand as I learnt lot of skills in less time. Also, they had arranged a professional training on mongoDB for me which was pretty cool. Apart from these technical internships, I have also worked for few organizations doing marketing, business development. These include Internshala, Faadooengineers etc.

Apart from these internships, I had started a company during my second year (notemybook) and continued it for 2 years until I decided to pursue Machine Learning as my career for time being. We won many business plan competitions and also got featured by Hindustan Times as Top under-19 CEOs and by Yourstory as Top 9 student startups that became big companies. We got featured by other publications like VCCircle, techaloo, thecampusentrepreneur, Inc42, Foradian etc. My passion for entrepreneurship helped me start an Entrepreneurship Cell for 2 years with help of my alumni. We conducted many events and competitions and became Mumbai’s Top 3 E-Cells within 3 months of its inception.

IF: What are your key gains and takeaways from this internship?

DS: This internship at Teach For India made me aware about the power of Machine Learning. The capability of saving 2400+ hours for an organization with few lines of code is just amazing in itself. After this internship, I gained lot of confidence in not only just technical skill but also in skill of recognizing problems that have potential to be solved by Machine Learning. I feel the latter skill is more important to have for any programmer to be successful because in today’s world where there is immense competition, just having a programming skill is like not having it. This was my biggest takeaway from this internship.   

IF: Advice for juniors? Which can help them in getting internships in their future college life and also advice for making the best out of it.

DS: My advice for juniors would be find their passion as soon as possible. This can be attainable only if you explore and read about more and more things in your first two years of college life. Once you are aware of this passion, start pursuing it. There are many ways to get an internship in your field of interest. One way is to use contact which I feel is very efficient and time saving and also you may end up in a firm with a big brand. If not, then you must first start with lesser brand firms and then by the end of your undergraduate, you will definitely end up with a big one. Sure shot mantra for a great profile is to plan and start early. Now, once you land with an internship, give your 100% and make sure to be in touch with your mentor even after your internship. You never know when they may come handy.

Lastly, don’t do anything for just its tag attached to it or just to build your profile. Most of the times, it doesn’t work. Recognize your passion and work towards it. I myself have done 10+ internships including 2 international internships but none of them were to build my resume. I didn’t even sit for placements neither applied for MS. I wanted to gain as much exposure as I can as a student which I think only internships can provide. These experiences have definitely enhanced not only my technical skills but also my communication and leadership skills that will help in pursuing my passion of entrepreneurship once I graduate in May 2016.

IF: What are your future plans after this internship and how much impact will this internship have on it?

DS: From past 6 months, I have been working on a startup idea (Kernl) along with California based entrepreneurs to launch it in India. My role is to head India operations for next few years. So yeah, once I graduate, I will be working full time with it. This internship made me learn on how to recognize potential problems that could be solved using Machine Learning. So definitely, this skill will come in use for my startup as it is an app based one.

We’d like to thank Divyansh for this insightful interview and wish him all the best for his future endeavors. 

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