SitusAMC Junior Underwriter Interview Questions and Answers

Very basic aptitude questions in a live mettle like platform

Q1. Questions on regression and patient data.
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Q1. General check for cultural fit
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Q1. Scd type 1, 2,3,4
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Q2. Joins, left,right,full,cross
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Q1. General topics like previous projects and managerial questions
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Q2. Managerial questions to know you
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Q1. Salary discussion
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Q2. Culture about Axtria and policies
Ans. 
Axtria promotes a collaborative and inclusive culture with a focus on innovation and growth.
• Axtria values diversity and inclusion in the workplace

• The company encourages innovation and creativity

• There are policies in place to support employee growth and development

• Axtria promotes a collaborative work environment
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Simple test with basic questions and reasoning.

Q1. Mostly based on resume and sql questions along with some easy questions related to project .
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Q2. Snowflake , Python SQL joins ? Tbl A ->1,1,1,null Tbl B ->1,null,1,1 What will be the output for each join and write those outputs.
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Q1. Techno Managerial round mostly focused on sql , and database design .
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Q2. You would be given a scenario for which you would be asked to design a database and based on that design you will be asked few questions.
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Q3. Snowflake time travel ?
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Q1. Basic hr questions were asked .
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Q1. Was asked about day to day tasks and responsibilities. Technical skills and specifically forecasting and experience in forecasting and visualisation
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Online aptitude test with a moderate to hard difficulty

Q1. Was asked to explain certain processes and asked about market modeling approaches and how tools Like sql, python and excel can be used to derive at a particular forecast
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Q1. Salary negotiation
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Q1. Ridge and lasso regression difference
Ans. 
Ridge and lasso regression are both regularization techniques used in linear regression to prevent overfitting by adding penalty terms to the cost function.
• Ridge regression adds a penalty term equivalent to the square of the magnitude of coefficients, while lasso regression adds a penalty term equivalent to the absolute value of the magnitude of coefficients.

• Ridge regression tends to shrink the coefficients towards zer...read more
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Q2. Random forest vs decision tree vs xg boost
Ans. 
Random forest is an ensemble method using multiple decision trees, XGBoost is a gradient boosting algorithm that builds trees sequentially.
• Random forest is an ensemble learning method that builds multiple decision trees and combines their predictions.

• Decision tree is a single tree model that makes decisions based on features to predict outcomes.

• XGBoost is a gradient boosting algorithm that builds trees sequentially, op...read more
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Q1. Why do you not want to opt for higher studies
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Q2. What to do when a team member is not collaborating
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