Quadeye Quantitative Researcher Interview Questions and Answers

Q1. Stack based question Medium Difficulty DSA.
Add your answer
Q2. Theory questions related Java, Spring, OOPs
Add your answer

Q1. Medium-hard DSA question.
Add your answer
Q2. Project related questions
Add your answer
Q3. Design Patterns
Add your answer

Q1. Company fit questions
Add your answer

DSA + JAVA + Spring boot

LLD (bookmyshow) + DSA

Basic array question leetcode medium

Q1. Discussions on my work experience.
Add your answer
Q2. Understanding of the architecture of my current organization.
Add your answer

Q1. My current experience and my interests and goals
Add your answer

Q1. Swift basics and DSA ques
Add your answer

Q1. What is a logistic regression model?
Ans. 
Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.
• Logistic regression is used when the dependent variable is binary (0/1, True/False, Yes/No, etc.)

• It estimates the probability that a given input belongs to a particular category.

• The model calculates the odds of the event happening.

• It uses a logistic function to map the input values to ...read more
Answered by AI
Add your answer
Q2. Explain the random forest model.
Ans. 
Random forest is an ensemble learning method that builds multiple decision trees and merges them to improve accuracy and prevent overfitting.
• Random forest is a type of ensemble learning method.

• It builds multiple decision trees during training.

• Each tree is built using a subset of the training data and a random subset of features.

• The final prediction is made by averaging the predictions of all the individual trees.

• Random...read more
Answered by AI
Add your answer
Q3. Explain decision trees
Ans. 
Decision trees are a popular machine learning algorithm used for classification and regression tasks.
• Decision trees are a flowchart-like structure where each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome.

• They are easy to interpret and visualize, making them popular for exploratory data analysis.

• Decision trees can handle both numerical ...read more
Answered by AI
Add your answer

Q1. How do you see yourself in next 5 years?
Ans. 
In the next 5 years, I see myself growing into a senior data scientist role, leading projects and mentoring junior team members.
• Continuing to enhance my skills in data analysis, machine learning, and programming languages such as Python and R

• Taking on more responsibilities in project management and client interactions

• Working towards becoming a subject matter expert in a specific industry or domain

• Mentoring and guiding ...read more
Answered by AI
Add your answer
Q2. What are you 5 years back.what is the difference?
Ans. 
I was a student pursuing my undergraduate degree in Computer Science.
• 5 years back, I was studying Computer Science in college.

• Now, I have completed my degree and gained experience in data science through internships and projects.

• I have developed strong analytical and programming skills over the past 5 years.

• I have also learned new technologies and tools in the field of data science.

• I have a better understanding of real
Answered by AI
Add your answer

Q1. Knowledge about data summarisation.and some tools like Power bi and advance excel.
Add your answer