Sugoi Labs Interview Questions and Answers

It was a 60 minute aptitude test that had 60 qs to answer covering sections like quants, verbal, logical reasoning and some general programming. There was a 0.5 mark negative marking as well for each wrong answer. It was easy test

Q1. Resume based qs like what certifications you did, your best project till now
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Q2. An aptitude problem was also given related about relative speed concept to check logical thinking
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Q3. Analysis of xyz company customers invoice dataset
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Q4. Some gfg puzzles, basic probability
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Q1. Tell about family background
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Q2. What polestar does and why you want to be a part of the team?
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6 question 1 hard, 3 med, 2 easy

Q1. Rainwater PRoblem and multisource bfs
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Q1. Lru Cache leet problem in deep
Ans. 
Implement a Least Recently Used (LRU) cache
• Use a combination of a doubly linked list and a hashmap to efficiently implement the LRU cache

• When a new element is accessed, move it to the front of the linked list and update the hashmap

• When the cache is full, remove the least recently used element from the end of the linked list and the hashmap
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Q1. Multithreading is asked in deep
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Q1. Coalesce, SQL Order of Execution
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Q2. Given a table with fields(id, name, salary, managerId) find out the managers who have atleast 5 reportees under him/her.
Ans. 
Use SQL query to count number of reportees for each manager and filter out those with atleast 5 reportees.
• Write a SQL query to count number of reportees for each manager using GROUP BY clause

• Add HAVING clause to filter out managers with atleast 5 reportees

• Example: SELECT managerId, COUNT(id) AS num_reportees FROM table_name GROUP BY managerId HAVING num_reportees >= 5
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Q3. How to manage large datasets in python
Ans. 
Use libraries like pandas and dask to efficiently manage large datasets in Python.
• Use pandas library for data manipulation and analysis.

• Use dask library for parallel computing and out-of-core processing.

• Optimize memory usage by loading data in chunks or using data types efficiently.

• Consider using cloud services like AWS S3 or Google BigQuery for storing and processing large datasets.
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Q4. Name few of the commonly used python libraries used by DA
Ans. 
Some commonly used Python libraries for Data Analysts are Pandas, NumPy, Matplotlib, and Scikit-learn.
• Pandas - used for data manipulation and analysis

• NumPy - used for numerical computing and working with arrays

• Matplotlib - used for data visualization

• Scikit-learn - used for machine learning and data mining
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Q1. Behavior, worst personality, useless manager
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Q2. Always keeping eyes on girls one of the worst manager
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Q1. Questions about kubernetes and 5gc
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Q2. Containers and implementation of pods for 5gc
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Q1. Previous company and package negotiation
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