Clarivate Interview Questions, Process, and Tips

Test on Clinical trial info

Q1. Overall work details and questions on it
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Q1. They connected me about the willing to join the company
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Q2. They contacted for about pay confirmation and explained company rules
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Q3. How willing to join the company
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Subject related questions on indications

Q1. Questions related to your profile and job roles
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Q2. Explain clinical trial
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Round duration - 75 minutes
Round difficulty - Medium

Consists of MCQ + 2 coding questions( medium level)

Q1. 
Best Time to Buy and Sell Stock II Problem Statement
Given the stock prices for a certain number of days, represented as an array, determine the maximum profit you can achieve. You may perform as many tra...read more
Ans. 
The problem involves finding the maximum profit that can be achieved by buying and selling stocks on different days.
• Iterate through the array of stock prices and find the local minima and maxima to calculate profit

• Keep track of the total profit by adding the differences between consecutive maxima and minima

• You can perform multiple transactions, so buy at each local minima and sell at each local maxima

• Example: For price...read more
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Round duration - 60 minutes
Round difficulty - Easy

The round is based on data structures, oops concepts and implementation, OS and DBMS general questions. And Please do not forget to read about scheduling algorithms and ACID properties of RDBMS.

Q1. Can you explain the implementation of abstract classes and interfaces in inheritance, as well as the concepts of function overloading and overriding?
Ans. 
Abstract classes and interfaces in inheritance allow for defining common behavior and function signatures, while function overloading and overriding enable polymorphism.
• Abstract classes are classes that cannot be instantiated and may contain abstract methods that must be implemented by subclasses.

• Interfaces are similar to abstract classes but can only contain method signatures and constants, with no method implementati...read more
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Q1. What is Your project and what is your contribution
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Q2. Explain Manufacturing process
Ans. 
Manufacturing process involves transforming raw materials into finished products through a series of steps.
• Manufacturing process starts with the procurement of raw materials.

• Raw materials are then processed or transformed into intermediate products.

• Intermediate products are further processed and assembled to create the final product.

• Quality control measures are implemented throughout the process to ensure product stand...read more
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Q3. Define Casting Process
Ans. 
Casting process is a manufacturing technique used to shape molten metal into a desired form by pouring it into a mold.
• Casting process involves melting a metal and pouring it into a mold.

• The molten metal solidifies inside the mold and takes its shape.

• Different types of casting processes include sand casting, investment casting, and die casting.

• Casting is commonly used in the manufacturing of automotive parts, jewelry, a
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Q4. What is Knurling
Ans. 
Knurling is a process of creating a pattern of ridges or grooves on a surface for improved grip or aesthetics.
• Knurling is commonly used on tools, handles, and knobs to provide a better grip.

• It involves pressing a pattern of ridges or grooves onto a surface using a knurling tool.

• Knurling can be done on various materials such as metal, plastic, or wood.

• The pattern created by knurling can be diamond-shaped, straight, or d...read more
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Q1. What are strengths and weakness
Ans. 
My strengths include strong analytical skills and attention to detail. My weaknesses include public speaking and time management.
• Strengths: Strong analytical skills

• Strengths: Attention to detail

• Weaknesses: Public speaking

• Weaknesses: Time management
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Q1. Only technical questions were asked.
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Q2. All the quations were based on detailed knowledge on patents
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Q1. Asked to explain previous projects. How that impacts the business
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Q2. How random forest is bettercthan decision tree
Ans. 
Random forest is better than decision tree due to its ability to reduce overfitting and handle large datasets.
• Random forest reduces overfitting by averaging multiple decision trees

• Random forest can handle large datasets with high dimensionality

• Random forest is more robust to noise and outliers compared to a single decision tree
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Q3. Assumptions of linear regression
Ans. 
Assumptions of linear regression include linearity, independence, homoscedasticity, and normality.
• 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.
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Q1. Why do you want to join Clarivate
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Q2. Why are you leaving previous organization
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