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I appeared for an interview in Nov 2024.
To increase business revenue from 15 million to 20 million, focus on expanding product offerings, improving marketing strategies, optimizing pricing, enhancing customer experience, and exploring new sales channels.
Expand product offerings to attract new customers and increase sales
Improve marketing strategies to reach a wider audience and drive more traffic to the store
Optimize pricing strategies to maximize profits wi...
I have extensive experience in retail management, a proven track record of increasing sales and improving store operations, and a strong focus on customer satisfaction.
10+ years of experience in retail management
Increased sales by 20% in my previous role
Implemented new training programs that improved employee performance
Received multiple awards for outstanding customer service
I earned $60,000 in my last role. I am looking for a salary in the range of $70,000-$80,000 for this position based on my experience, skills, and the responsibilities of the role.
Last salary was $60,000
Expecting $70,000-$80,000 based on experience and responsibilities
Justification includes my skills, experience, and the market rate for the position
I applied via Walk-in and was interviewed in Oct 2022. There were 2 interview rounds.
I applied via Referral and was interviewed before Jan 2021. There was 1 interview round.
I applied via Campus Placement and was interviewed before May 2021. There were 2 interview rounds.
Numerical ability and logical reasoning followed by some coding mcqs
Printing 1 to 100 without for loop
Use recursion to print numbers from 1 to 99
Print 100 outside the recursion
Use a base case to stop recursion at 100
I applied via Campus Placement and was interviewed before Jun 2021. There were 2 interview rounds.
Simple aptitude test
I applied via Recruitment Consultant and was interviewed before Jul 2020. There was 1 interview round.
I applied via Naukri.com
I applied via Newspaper Ad and was interviewed before Jun 2021. There were 3 interview rounds.
I appeared for an interview in Aug 2017.
Merge Sort is a divide and conquer algorithm that sorts an array by dividing it into two halves, sorting them separately, and then merging the sorted halves.
Divide the array into two halves
Recursively sort the two halves
Merge the sorted halves
Find pairs of integers in a BST whose sum is equal to a given number.
Traverse the BST and store the values in a hash set.
For each node, check if (X - node.value) exists in the hash set.
If yes, add the pair (node.value, X - node.value) to the result.
Continue traversal until all nodes are processed.
Merge overlapping time intervals into mutually exclusive intervals.
Sort the intervals based on their start time.
Iterate through the intervals and merge overlapping intervals.
Output the mutually exclusive intervals.
Example: [(1,3), (2,6), (8,10), (15,18)] -> [(1,6), (8,10), (15,18)]
Different types of hashing and alternative for Linear Chaining
Different types of hashing include division, multiplication, and universal hashing
Alternative for Linear Chaining is Open Addressing
Open Addressing includes Linear Probing, Quadratic Probing, and Double Hashing
An AVL tree is a self-balancing binary search tree where the heights of the left and right subtrees differ by at most one.
AVL tree is a binary search tree with additional balance factor for each node.
The balance factor is the difference between the heights of the left and right subtrees.
Insertion and deletion operations in AVL tree maintain the balance factor to ensure the tree remains balanced.
Rotations are performed ...
Find the minimum number of squares whose sum equals to a given number n.
Use dynamic programming to solve the problem efficiently.
Start with finding the square root of n and check if it is a perfect square.
If not, then try to find the minimum number of squares required for the remaining number.
Repeat the process until the remaining number becomes 0.
Return the minimum number of squares required for the given number n.
Insertion sort for a singly linked list.
Traverse the list and compare each node with the previous nodes
If the current node is smaller, swap it with the previous node
Repeat until the end of the list is reached
Time complexity is O(n^2)
based on 3 interviews
Interview experience
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