Compunnel Interview Questions, Process, and Tips

Q1. Past experience and relevancy
Add your answer

Q1. Experience and situations
Add your answer

Q1. I applied for a project manager position, my questions were a mix of project manager mentioned and business analysis.
Add your answer

Q1. Another technical round with a different person. More detailed questions on project management and business analysis with some behavioural questions.
Add your answer

Q1. This was a Fitment round
Add your answer

Q1. Questions Related to Previous Experience and tools
Add your answer

Q1. 1. Measures of Dispersion
Ans. 
Measures of Dispersion are used to describe the spread of data around the central tendency.
• Measures of Dispersion include Range, Variance, Standard Deviation, and Interquartile Range.

• Range is the difference between the maximum and minimum values in a dataset.

• Variance measures how far each value is from the mean.

• Standard Deviation is the square root of the variance.

• Interquartile Range is the difference between the 75th
Answered by AI
Add your answer
Q2. Difference between Linear & Logistic Regression ? Give examples ?
Ans. 
Linear regression is used for continuous data while logistic regression is used for categorical data.
• Linear regression predicts a continuous outcome while logistic regression predicts a probability of an event occurring.

• Linear regression uses a straight line to fit the data while logistic regression uses an S-shaped curve.

• Linear regression is used for predicting values like house prices while logistic regression is use...read more
Answered by AI
Add your answer
Q3. What is Feature Selection & Feature Engineering
Ans. 
Feature selection is the process of selecting relevant features from a dataset, while feature engineering involves creating new features.
• Feature selection helps to reduce the dimensionality of the dataset and improve model performance.

• Feature engineering involves transforming or combining existing features to create new ones that may be more informative.

• Examples of feature engineering include creating interaction terms...read more
Answered by AI
Add your answer
Q4. What is Gradient Descent and where is it used
Ans. 
Gradient Descent is an optimization algorithm used to minimize the cost function of a machine learning model.
• Gradient Descent is used in machine learning to find the optimal parameters of a model by minimizing the cost function

• It works by iteratively adjusting the parameters in the direction of steepest descent of the cost function

• There are two types of Gradient Descent: Batch Gradient Descent and Stochastic Gradient D...read more
Answered by AI
Add your answer
Q5. What are different types of machine learning with examples
Ans. 
There are three types of machine learning: supervised, unsupervised, and reinforcement learning.
• Supervised learning involves training a model on labeled data to make predictions on new data. Example: predicting house prices based on features like location, size, etc.

• Unsupervised learning involves finding patterns in unlabeled data. Example: clustering customers based on their purchasing behavior.

• Reinforcement learning ...read more
Answered by AI
Add your answer

Q1. Experience in US Staffing
Add your answer
Q2. How do you approach prospects? Sales Strategy
Ans. 
I approach prospects with research, personalized outreach, and a focus on building relationships to drive sales success.
• Conduct thorough research on the prospect's industry and pain points to tailor my approach.

• Utilize social media platforms like LinkedIn to connect and engage with prospects before reaching out.

• Craft personalized emails that address specific needs and demonstrate how our solutions can help.

• Follow up wi...read more
Answered by AI
Add your answer

1 hour assessment and coding test related to Job Duties

Q1. Spring AOP cross cutting concerns implementation
Add your answer
Q2. Experience with AWS SQS, S3, CloudFront, RDS, Aurora, Lambda.
Ans. 
Experience with various AWS services like SQS, S3, CloudFront, RDS, Aurora, and Lambda.
• Experience setting up and managing SQS for message queuing

• Experience using S3 for scalable storage solutions

• Experience configuring CloudFront for content delivery

• Experience working with RDS and Aurora for database management

• Experience developing serverless applications with Lambda functions
Answered by AI
Add your answer

Q1. Where do you see yourself in the next 5 years in compunnel staffing?
Add your answer