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Ernst & Young Data Scientist Staff Interview Questions and Answers
Ernst & Young Data Scientist Staff Interview Experiences
1 interview found
Anonymous
Selected
I applied via Referral and was interviewed before Jun 2022. There were 4 interview rounds.
Generic case description on type of projects i have worked on with detailed explanation on what tasks were performed and my role in the project.
(3 Questions)
- Q1. What various techniques have u worked on? Statistical methods approach etc.
- Ans.
I have worked on various techniques including statistical methods, machine learning algorithms, and data visualization.
Statistical methods such as regression analysis, hypothesis testing, and ANOVA
Machine learning algorithms like decision trees, random forests, and neural networks
Data visualization tools like Tableau, Power BI, and matplotlib
- Q2. Can you explain how and when you have used linear regression? A full 40 min discussion on this alone with all possible in and out details on model building, validation and debugging of linear models in gen...
- Q3. A few programming questions in python on syntax on list comprehension and basic list operations. Nothing major
(1 Question)
- Q1. Basic discussion on other types of projects done along with techniques used. More techno HR round really emphasis on architectural approach building and problem solving.
Interview Preparation Tips
- Machine Learning
- Python
- Data Analysis
- Problem Solving
- Data Science
- model validation
- model evaluation and training
Interview questions from similar companies
Manas Sharma
(1 Question)
- Q1. What is xgboost algorithm
- Ans.
XGBoost is a powerful machine learning algorithm known for its speed and performance in handling large datasets.
XGBoost stands for eXtreme Gradient Boosting
It is an implementation of gradient boosted decision trees designed for speed and performance
XGBoost is widely used in machine learning competitions and real-world applications
It can handle missing data, regularization, parallel processing, and custom optimization o...
Selected
I applied via Approached by Company and was interviewed in May 2024. There were 3 interview rounds.
DSA was asked. And general coding language questions were asked. Previous experience based questions were asked.
Machine Learning, Generative AI, Deep learning interview questions. 2 Coding problems based on Algorithms.
(3 Questions)
- Q1. One systems design question was there.
- Q2. Situations based problems was there.
- Q3. Questions on Past experiences.
Hemant Yadav
Selected
I applied via Approached by Company and was interviewed in Oct 2024. There were 2 interview rounds.
Combination logic on python
(1 Question)
- Q1. Explain classification
- Ans.
Classification is a machine learning technique used to categorize data into different classes or categories based on past observations.
Classification involves training a model on labeled data to predict the class of new, unseen data points.
Common algorithms for classification include logistic regression, decision trees, support vector machines, and k-nearest neighbors.
Examples of classification tasks include spam email...
(1 Question)
- Q1. ML, DL, Data Science, Python
(1 Question)
- Q1. AI,ML, Data Science, Use cases
Machine Learning, Metrics
Selected
I applied via Approached by Company and was interviewed before May 2023. There were 2 interview rounds.
(1 Question)
- Q1. 1. What is the role of beta value in Logistic regression? 2. What is bias variance trade off? 3. How did you decide on the list of variables that would be used in a model?
- Ans.
Beta value in logistic regression measures the impact of independent variables on the log odds of the dependent variable.
Beta value indicates the strength and direction of the relationship between the independent variables and the log odds of the dependent variable.
A positive beta value suggests that as the independent variable increases, the log odds of the dependent variable also increase.
A negative beta value sugges...
1. You are the data scientist of a digital store. You have to recommend top 10 products to a customer. What variables and techniques will you use to recommend the top 10 products?
Interview Preparation Tips
Skills evaluated in this interview
Selected
I applied via Approached by Company and was interviewed before Sep 2023. There were 3 interview rounds.
Simple Data Science Case Study
(1 Question)
- Q1. Python knowledge related questions
Data Science Case Study
Selected
I applied via Company Website and was interviewed before Sep 2022. There were 4 interview rounds.
(1 Question)
- Q1. Asked questions regarding my current role and responsibilities
(1 Question)
- Q1. Lots of questions related to Data Science coding test
(1 Question)
- Q1. Taken two rounds of test to check cultural and team fitment.
It was on HackerRank
Building a reward points model.
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