Basic Information

• Name: Manisha Sahu
• Branch: BTech
• Company: MasterCard
• Duration: May 18 - Jul 18

Domain Targeted

I was focusing on Core (digital/microprocessor) in electrical engineering and I kept AIML field as backup as I am also pursuing minor in Cminds

Preparation Resources

For digital and microprocessor, went through Arya Vishe’s notes and also read Static Timing Analysis. Went through VHDL and Assembly codes too. Went through different online websites to solve questions (I just searched the topic names and solved randomly). Apart from that I also searched company specific pyqs for tests and interviews and talked to the seniors who got selected for that particular company’s interview rounds for interview rounds

For AIML, I did a basic ML course in summers and mentioned it in resume and revised all the basic terms related to linear regression, CNN, data science in general. DS 203, DS 303 and EE 353 notes were helpful to know what topics to read. Apart from this, for tests I practiced reasoning problems and DSA coding. Learnt SQL too. And particularly for analytics, practiced the probability puzzle questions from a website from which most of the questions were asked in interviews (Brainstellar).

And in general, I was thourough with my resume for both the profiles.

Interview Experience

Google(hardware) 1st round: intro, a basic question on logic using gates, pipeline timings, some more digital logic questions (and asked at end if I had any question) 2nd round: question about pipeline in more depth, and a VHDL code to be written for synchronous/asynchronous clock

NVIDIA: intro, a question on data science as I mentioned my minor, a question on STA, another question on Multiprocessor in Assembly code, a analytical question

Texas instrument: digital profile: asked parameters that are considered in production of microprocessor, a STA question, an Assembly code.

American express: intro, and a probability puzzle question (similar question was there in Brainstellar, I was eliminated in first round)

MasterCard : 1st round: the interviewer went through my resume and asked the definition of basic terms that I highlighted in my resume in data science and asked questions about clustering. 2nd round: a question about how to solve a practical problem using data science, a HR question about teamwork.

Other Applications

I applied for American express for data analytics profile, although it was not exactly on ML side

Project Work

I was working on a research paper on the topic of imbalance data in graphs (imbalance node classification). Basically I went through different existing research papers on the topic, brainstormed different ideas, suggested some new parameters and later on tried to implement the idea in public datasets

Overall Experience

I had a great experience here. The work balance was chill. The work environment was friendly. Although I was hesitant a bit to explore more fields in the company, the whole team is very open to answer your curiosity and also gave insights on all other different field and products that has been developed/developing in the company.

Organizational Culture

The whole team was welcoming and nice. We can ask any query/help to anyone and they helped really nicely. The office space was nice too (There was no designated place for anyone so we were allowed to sit on any desk and work, it was a hybrid mode of work too, no specified in and out was there). And my peers/co-interns were eager to learn new things too. We always discussed with one another about the topics we worked on.

Networking Opportunities

Yes, there were many leadership talks, speed networking, and regular all team meets too. We had an office party too.

PPO & Future Prospects

The company is really eager on hiring interns as full time. The company offers PPO to almost all of the interns based on their performance

Recommendation & Advice

Yes, I would recommend it if you want to explore the field of data science and also have a taste of both research field and building AIML products