PolicyBazaar Sales Person Interview Questions and Answers

Q1. About your self About Family Hobbies Education
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Q2. About self, education, skill, job relited qu.
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Q1. HR Round. What your skill
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Q2. Name. Address. Family
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Q3. Name, Address, Education
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Good advice to the Aptitude test.

Q1. Tell me about yourself.
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Q2. What is the Job profile
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There was a test conducted by recruiters

In Group discussion there were asked many questions and we have to ans in fast manner

Q1. Tell me about yourself
Ans. My name is sweety Rajoriya and I am 21 year old. For the past 1 year, I've been working as a Data entry & Accounts at a company. I have just completed my studies from graduate.
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Round duration - 60 Minutes
Round difficulty - Medium

The round was held on Google Meet and I was given 2 coding problems for which first I had to explain my approach and then I had to write code in Shared Google Docs and dry run on sample test cases and discuss Time and Space Complexity.

Q1. 
Validate BST Problem Statement
Given a binary tree with N nodes, determine whether the tree is a Binary Search Tree (BST). If it is a BST, return true; otherwise, return false.
A binary search tree (BST)...read more
Ans. 
Validate if a given binary tree is a Binary Search Tree (BST) or not.
• Check if the left subtree of a node contains only nodes with data less than the node's data.

• Check if the right subtree of a node contains only nodes with data greater than the node's data.

• Recursively check if both left and right subtrees are also binary search trees.
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Q2. 
Maximum Sum Path from Leaf to Root
Given a binary tree with 'N' nodes, identify the path from a leaf node to the root node that has the maximum sum among all root-to-leaf paths.
Example:
All the possibl...read more
Ans. 
Find the path from a leaf node to the root node with the maximum sum in a binary tree.
• Traverse the binary tree from leaf to root while keeping track of the sum of each path.

• Compare the sums of all paths and return the path with the maximum sum.

• Use recursion to traverse the tree efficiently and keep updating the maximum sum path.
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Round duration - 60 Minutes
Round difficulty - Medium

This was also a Data Structures and Algorithms round where I was asked to solve 2 coding problems explaining my approach with proper Complexity Analysis . After the coding questions were over there was some time left so the interviewer asked me some concepts related to DBMS.

Q1. 
Next Permutation Problem Statement
You are given a permutation of 'N' integers. A sequence of 'N' integers is considered a permutation if it includes all integers from 1 to 'N' exactly once. Your task is ...read more
Ans. 
The task is to rearrange a given permutation of 'N' integers to form the lexicographically next greater permutation.
• Iterate from right to left to find the first element that is smaller than the element to its right.

• Swap this element with the smallest element to its right that is greater than it.

• Reverse the elements to the right of the swapped element to get the lexicographically next greater permutation.
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Q2. 
Largest BST Subtree Problem Statement
You are given a binary tree with 'N' nodes. Your task is to determine the size of the largest subtree within the binary tree which is also a Binary Search Tree (BST).
...read more
Ans. 
Find the size of the largest subtree in a binary tree that is also a Binary Search Tree.
• Traverse the tree in a bottom-up manner to check if each subtree is a BST.

• Keep track of the size of the largest BST subtree encountered so far.

• Use recursion to solve this problem efficiently.

• Example: For the input 1 2 3 4 -1 5 6 -1 7 -1 -1 -1 -1 -1 -1, the largest BST subtree has a size of 3.
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Q3. Can you explain indexing in databases?
Ans. 
Indexing in databases is a technique used to improve the speed of data retrieval by creating a data structure that allows for quick lookups.
• Indexes are created on columns in a database table to speed up the retrieval of rows that match a certain condition.

• Types of indexes include B-tree, hash, and bitmap indexes.

• Indexes can improve the performance of SELECT queries but may slow down INSERT, UPDATE, and DELETE operation...read more
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Round duration - 50 Minutes
Round difficulty - Medium

This round also had 2 questions related to DS and Algo . One was from graphs and the other was an implementation of a LRU Cache . There were 2 interviewers and both of them were quite friendly and helpful. Overall, this round went well.

Q1. 
Detect Cycle in a Directed Graph
You are provided with a directed graph composed of 'N' nodes. You have a matrix called 'EDGES' with dimensions M x 2, which specifies the 'M' edges in the graph. Each edge...read more
Ans. 
Detect cycle in a directed graph using depth-first search (DFS) algorithm.
• Use DFS to traverse the graph and detect back edges (edges that point to an ancestor node).

• Maintain a visited array to keep track of visited nodes and a recursion stack to keep track of nodes in the current path.

• If a back edge is found during traversal, a cycle exists in the graph.

• Return true if a cycle is detected, false otherwise.
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Q2. 
LRU Cache Design Question
Design a data structure for a Least Recently Used (LRU) cache that supports the following operations:
1. get(key) - Return the value of the key if it exists in the cache; otherw...read more
Ans. 
Design a Least Recently Used (LRU) cache data structure that supports get and put operations with capacity constraint.
• Use a combination of hashmap and doubly linked list to efficiently implement the LRU cache.

• Keep track of the least recently used item and update it accordingly when inserting new items.

• Ensure to handle the capacity constraint by evicting the least recently used item when the cache is full.

• Implement get(...read more
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