L&T NxT | Data Scientist

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Interview Experiences

L&T NxT | Data Scientist

1 Aug 2020 | Bhushan Shewale

About LnT NxT :  Larsen & Toubro (L&T) is an over $21 billion engineering, construction, manufacturing, information technology and financial services multinational conglomerate, with operations in more than 30 countries and manufacturing in eight of them . Over the past 3+ years, L&T group has undertaken a large scale digital transformation of their own businesses and have realized significant benefits with proven ROI. L&T-NxT leverages the group’s deep industry domain expertise, leading edge information technology capabilities and the invaluable learning from the digital transformation of their own diverse businesses, to deliver disruptive digital outcomes for their global customers.

 

Interviewing for Role : Data Scientist

 

Key Skills Required : Machine Learning, Data Pre-processing, EDA, NLP, Python/R

 

Round 1 | Telephonic Interview by HR

It all started with this one question “Tell me something about yourself” and then went on to discussing what was written in my resume.

Things we discussed:

(1) My background, prior experience and how soon can I join

(2) Projects that I have mentioned on resume and the technicals skills that I have worked on

(3) If I am open to relocate and learn additional skills on the job

 

Round 2 | Video Interview by Technical Expert

This round went on for close to 40 mins and the main objective was to test my basics and the same time understand the kind of problems I have worked on

(a) The first question was around the project that I had worked on in the recent past.

(b) Why did I go for the approach and some explain some other approach that can also be used to solve the same problem.

(c) Questions around EDA and feature selection on the project I talked about

(d) Pick an algorithm and explain inside out

(e) If you have 4 algo – DT, SVM, Random Forest, Logistic Regression, GB – all have accuracy, F1 score 88-90. Which model will you deploy and why

(i) Question around

(ii) Random Forest

(iii) SVM & GVM

(iv) Categorical data

(v) What does Business want/needs & its connection with Data Science problems

(f) Interviewer was very interested in understanding what is the learning curve for me in Data Science to which I spoke about how I am learning deep learning and a project that I would like to build

 

Round 3 | Hiring Challenge

In this round I got a very open ended problem statement where in a data set with 5 variables was given and was asked to give insights using EDA. Time given to solve was 48 hours.

 

Round 4 | Final Technical round by Head of Data Science

This is a pure technical round focused to understand the tech skills, projects build and NLP knowledge

Questions asked:

(1) Explain a project end to end that you have build with follow-up questions on approach and mathematical explanations

(2) Hiring Challenge solution was discussed

(3) My strengths in Data Science and a lot of follow-up questions on the same

(4) NLP basic questions

 

Final HR round

This was a pure salary negotiation discussion

 

Final Outcome : SELECT

 

What I think worked for me

The NLP project and the skills that I built over the course helped me alot. When I explained the NLP project the interviewer mentioned that they are working on something similar and I think that was one thing that worked for me.

Knowing inside out of the projects that you have built and mentioned in your resume is very very important. You should be able to explain not just the approach but why did you take the approach.

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