HCL Tech

Role: Data Scientist

College: Not Specified

Interview Date: February 1, 2025

Interview Type: Online (MS Teams)

Result: Cleared Round 1

Difficulty: Medium to Hard

Rounds: 1 round (described)

Topics Asked: Machine Learning projects, Dimensionality reduction (multicollinearity, feature selection, PCA), Machine Learning models (Timeseries Forecasting, Recommendation Systems), Non-stationarity in time series, Hyperparameter tuning (GridSearchCV), GenAI and LLMs (authentication, OpenAI library, prompting skills).

Experience:

This interview was for a Data Scientist position at HCL Tech, applied through Naukri.com. The interview was conducted online via MS Teams.

Round 1: Technical Interview
The interview began with a basic introduction of education and work history, followed by an explanation of a machine learning project the candidate had worked on.

Technical discussions included:

• How to reduce dimensionality with 4000 columns/features and 1 target variable (discreet or continuous), explaining methods like eliminating multicollinearity, feature selection, and PCA.
• Discussion about known machine learning models, focusing in-depth on timeseries forecasting and non-stationarity.
• Hyperparameter tuning methods, specifically GridSearchCV, its workings, and considerations.

A real-time coding challenge was given where the candidate shared their screen and VSCode.

Coding Question: Given a comma-separated text file where the first row is a column title and remaining rows are numbers separated by commas, perform a row-wise sum of all digits without using any standard library.

Finally, the interviewer asked about experience in GenAI and LLMs, to which the candidate replied briefly about the authentication process of the OpenAI library and how to use it to train LLMs with good prompting skills. The candidate was advised to focus more on GenAI if selected for the next round, as the proposed position demanded majority GenAI work.

Overall, it was a great interview experience.