SitusAMC Technical Specialist Interview Questions and Answers

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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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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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. 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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The Aptitude round was of mediocre level, get well prepared for it and it is a qualifying round

Q1. Project Related Questions
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Q2. Data Warehouse and modeling related questions, along with schema selection in various scenarios
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Q1. About Myself, Why Axtria, Pharma related questions
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Q2. Real life scenarios
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Q1. About IC design
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Q2. Resume based questions
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Logical, statistics, Aptitude, Data science and analytics

Q1. Difference between Delete and Truncate in SQL
Ans. 
Delete removes specific rows from a table, while Truncate removes all rows from a table.
• Delete is a DML command, while Truncate is a DDL command.

• Delete can be rolled back, while Truncate cannot be rolled back.

• Delete maintains the table structure and indexes, while Truncate resets the table structure and indexes.

• Delete triggers delete triggers and delete constraints, while Truncate does not trigger any triggers or const...read more
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Q2. Assumptions of regression
Ans. 
Assumptions of regression
• Linearity: The relationship between the independent and dependent variables is linear.

• Independence: The residuals are independent of each other.

• Homoscedasticity: The variance of the residuals is constant across all levels of the independent variables.

• Normality: The residuals are normally distributed.

• No multicollinearity: The independent variables are not highly correlated with each other.
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