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MU Company Decision Scientist Interview Questions and Answers
MU Company Decision Scientist Interview Experiences
1 interview found
Vagheesan Kesavan
Basic aptitude and scenario questions
Discussion of any business topic
(2 Questions)
- Q1. Resume walkthrough
- Q2. Statistics questions
Top trending discussions
Interview questions from similar companies
Anonymous
(2 Questions)
- Q1. Use case based question
- Q2. Explain tree models.
- Ans.
Tree models are predictive models that use a tree-like graph of decisions and their possible consequences.
Tree models split the data into subsets based on the most significant attributes.
They are used for classification and regression tasks.
Examples include decision trees, random forests, and gradient boosting trees.
(2 Questions)
- Q1. Use case based questions
- Q2. Project based questions, Segmentation, look alike modeling
(1 Question)
- Q1. Expected salary
- Ans.
Negotiable based on the responsibilities and benefits offered by the position.
Salary expectations are flexible and open for discussion.
Consider factors such as job responsibilities, benefits, and industry standards when determining salary expectations.
Provide a salary range if possible to allow for negotiation.
Research average salaries for similar positions in the industry to inform your expectations.
Skills evaluated in this interview
Decision Scientist Interview Questions & Answers
Amazon
ROSHIN JACOB JOHNSON me12b166
posted on 2 Dec 2016
I applied via campus placement at Indian Institute of Technology (IIT), Chennai and was interviewed in Dec 2016. There were 6 interview rounds.
Interview Questionnaire
2 Questions
- Q1. Most challenging problem you have solved or tried solving
- Ans.
Developing a predictive model for customer churn in a telecom company
Gathering and cleaning large amounts of customer data
Identifying key predictors of churn through statistical analysis
Building and testing various machine learning models
Iteratively refining the model to improve accuracy
Presenting findings and recommendations to stakeholders
- Q2. Few simple puzzles and guestimates
Interview Preparation Tips
Experience: Quant questions and basic programming
Duration: 45 minutes
Total Questions: 28
Round: Case Study Interview
Experience: Simple question. Just keep on telling what comes to your mind.
College Name: IIT Madras
Selected
I applied via Walk-in and was interviewed in Dec 2024. There were 5 interview rounds.
(1 Question)
- Q1. Resume screening Self introduction Roles and responsibilities
Given task Statics standard deviations Attrition Average of given table values and Given graph economi graph and poverty graph base on that need to gave answers 30 qustion and 60 min time duration
(2 Questions)
- Q1. Versant test should be need to attend Hirepro will have interview prosess in YouTube will check and prepare mid level hard
- Q2. We can goo for online prosess how it is
(1 Question)
- Q1. Manger Level round they will ask KPI NPS AHT standard deviations Service Level handling Root cause Analysis Weighted average Same product how will calculate Totall Swer % how will get Many of like bpi <20 ...
(1 Question)
- Q1. Salary discussion and update structure of our role and responsibilities
I applied via Naukri.com and was interviewed in Nov 2024. There was 1 interview round.
(5 Questions)
- Q1. What about your self?
- Q2. Family background
- Q3. Power BI test and advanced excel
- Q4. Microsoft access test
- Q5. Python test and One to one discussion with super boss
Selected
I applied via Campus Placement and was interviewed in Nov 2024. There were 3 interview rounds.
There were verbal, non verbal, reasoning , English and maths questions
(2 Questions)
- Q1. Tell me about your project.
- Ans.
I worked on a project analyzing customer behavior using machine learning algorithms.
Used Python for data preprocessing and analysis
Implemented machine learning models such as decision trees and logistic regression
Performed feature engineering to improve model performance
- Q2. What programming knowledge you have ?
- Ans.
Proficient in Python, R, and SQL with experience in data manipulation, visualization, and machine learning algorithms.
Proficient in Python for data analysis and machine learning tasks
Experience with R for statistical analysis and visualization
Knowledge of SQL for querying databases and extracting data
Familiarity with libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn
(2 Questions)
- Q1. Where do you stay ?
- Ans.
I currently stay in an apartment in downtown area.
I stay in an apartment in downtown area
My current residence is in a city
I live close to my workplace
- Q2. Tell me about you
- Ans.
I am a data science enthusiast with a strong background in statistics and machine learning.
Background in statistics and machine learning
Passionate about data science
Experience with data analysis tools like Python and R
I was interviewed in Oct 2024.
(1 Question)
- Q1. Project related questions from your CV
(2 Questions)
- Q1. Question on transformers
- Q2. Comparison of transfer learning and fintuning.
- Ans.
Transfer learning involves using pre-trained models on a different task, while fine-tuning involves further training a pre-trained model on a specific task.
Transfer learning uses knowledge gained from one task to improve learning on a different task.
Fine-tuning involves adjusting the parameters of a pre-trained model to better fit a specific task.
Transfer learning is faster and requires less data compared to training a...
Skills evaluated in this interview
Selected
I applied via Approached by Company and was interviewed in Aug 2024. There were 2 interview rounds.
*****, arjumpudi satyanarayana
(5 Questions)
- Q1. What is the python language
- Ans.
Python is a high-level programming language known for its simplicity and readability.
Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.
It emphasizes code readability and uses indentation for block delimiters.
Python has a large standard library and a vibrant community of developers.
Example: print('Hello, World!')
Example: import pandas as pd
- Q2. What is the code problems
- Ans.
Code problems refer to issues or errors in the code that need to be identified and fixed.
Code problems can include syntax errors, logical errors, or performance issues.
Examples of code problems include missing semicolons, incorrect variable assignments, or inefficient algorithms.
Identifying and resolving code problems is a key skill for data scientists to ensure accurate and efficient data analysis.
- Q3. What is the python code
- Ans.
Python code is a programming language used for data analysis, machine learning, and scientific computing.
Python code is written in a text editor or an integrated development environment (IDE)
Python code is executed using a Python interpreter
Python code can be used for data manipulation, visualization, and modeling
- Q4. What is the project
- Ans.
The project is a machine learning model to predict customer churn for a telecommunications company.
Developing predictive models using machine learning algorithms
Analyzing customer data to identify patterns and trends
Evaluating model performance and making recommendations for reducing customer churn
- Q5. What is the lnderssip
- Ans.
The question seems to be incomplete or misspelled.
It is possible that the interviewer made a mistake while asking the question.
Ask for clarification or context to provide a relevant answer.
Interview Preparation Tips
- Python
- Machine Learning
Skills evaluated in this interview
I applied via Approached by Company and was interviewed in Sep 2024. There was 1 interview round.
(2 Questions)
- Q1. Gave one easy question and asked what will be the output
- Q2. Leetcode 2 sum question
Interview Preparation Tips
I applied via Naukri.com and was interviewed in Sep 2024. There were 2 interview rounds.
(3 Questions)
- Q1. Overfitting and Underfitting
- Q2. Find Nth-largest element
- Ans.
Find Nth-largest element in an array
Sort the array in descending order
Return the element at index N-1
- Q3. NLP Data preprocessing
(2 Questions)
- Q1. Salary Discussion
- Q2. Fitment discussion
Skills evaluated in this interview
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MU Company Decision Scientist Interview Process
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