MetLife

Role: Machine Learning Intern

College: Not Specified (On-Campus)

Interview Date: September 26, 2019

Interview Type: On-Campus Internship

Result: Selected

Difficulty: Medium

Rounds: 2 rounds

Topics Asked: Probability, Statistics, Python/R Syntax, Machine Learning, Data Science, Deep Learning, DBMS, OS, Hadoop, SQL Queries

Experience:

PNB MetLife visited the campus for Machine Learning Interns. The selection process consisted of an Online Test followed by a Telephonic Interview.

Round 1: Online Test
The online test had four parts:

• Part 1: 15 questions on Probability and Statistics.
• Part 2: 15 questions on basic Python and R syntax.
• Part 3: 15 questions on Machine Learning and Data Science.
• Part 4: 15 questions on DBMS, OS, Hadoop, and SQL queries.

18 students cleared this round.

Round 2: Telephonic Interview
The interview began with the standard "tell me about yourself" question, followed by a detailed discussion of the candidate's projects. Since one project involved Deep Learning, the interviewer delved into Deep Learning concepts such as filters, pooling, flattening, Softmax, and dense layers, and asked about the implementation of backpropagation. Questions on Machine Learning algorithms, mainly Random Forest and Naive Bayes, and their Python implementation were also asked.

The interviewer then described a dataset with details and expected outcomes, asking the candidate how they would preprocess the dataset and what algorithm they would use to get the desired output. SQL queries like LEFT JOIN, RIGHT JOIN, and the use of LIKE and HAVING clauses were also covered. The interviewer inquired about Python experience, asking about tuples, the speed comparison between tuples and lists, immutable objects, classes, and inheritance implementation in Python.

3 students, including the interviewee, were selected for the internship.