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Morningstar Data Scientist Interview Questions and Answers
Morningstar Data Scientist Interview Experiences
1 interview found
Anonymous
Selected
I applied via Company Website and was interviewed before Aug 2023. There were 2 interview rounds.
(2 Questions)
- Q1. What is Bert and transformer
- Ans.
Bert and transformer are models used in natural language processing for tasks like text classification and language generation.
Bert (Bidirectional Encoder Representations from Transformers) is a transformer-based model developed by Google for NLP tasks.
Transformer is a deep learning model architecture that uses self-attention mechanisms to process sequential data like text.
Both Bert and transformer have been widely use...
- Q2. NLP pre processing techniques
- Ans.
NLP pre processing techniques involve cleaning and preparing text data for analysis.
Tokenization: breaking text into words or sentences
Stopword removal: removing common words that do not add meaning
Lemmatization: reducing words to their base form
Normalization: converting text to lowercase
Removing special characters and punctuation
(2 Questions)
- Q1. Basic questions
- Q2. Strength weakness
Skills evaluated in this interview
Data Scientist Jobs at Morningstar
Interview questions from similar companies
Selected
I applied via Approached by Company and was interviewed in Mar 2023. There were 3 interview rounds.
Develop an ML solution from the given problem statement and data.
(3 Questions)
- Q1. Discussion on your assignment and previous work.
- Q2. Why did you choose the model?
- Q3. Explain how GBM works
- Ans.
GBM is a machine learning algorithm that builds multiple decision trees to predict outcomes and combines them to improve accuracy.
GBM stands for Gradient Boosting Machine
It builds multiple decision trees sequentially, each one correcting errors made by the previous tree
The final prediction is a combination of predictions from all the trees
GBM is an ensemble learning technique that is popular for its high accuracy and f
Interview Preparation Tips
Skills evaluated in this interview
I applied via LinkedIn and was interviewed in Aug 2022. There were 5 interview rounds.
(1 Question)
- Q1. General resume based question. Interviewer asked me to explain one of the past project and asked some questions based on that
It was the assignment including the data science problem and SQL questions for one of the datetime table. Assignment was for 3 hours and had to complete some mandatory questions from data science assignment.
(1 Question)
- Q1. It was a technical + data science case study round. Interviewer asked me some technical questions based on machine learning and gave me one case study.
(1 Question)
- Q1. Interviewer asked me some general behavioural questions and also gave me one case study to solve.
Interview Preparation Tips
(1 Question)
- Q1. How to check model performance? Over fit vs underfit?
- Ans.
Model performance can be checked using various metrics such as accuracy, precision, recall, F1 score, and confusion matrix.
Split data into training and testing sets
Train the model on the training set
Evaluate the model on the testing set using metrics such as accuracy, precision, recall, F1 score, and confusion matrix
If the model performs well on the testing set, it is not overfit or underfit
If the model performs well o...
Python code for 45 mins. Pandas , group by , filtering questions
(1 Question)
- Q1. Mostly behavioral questions
Interview Preparation Tips
Skills evaluated in this interview
Selected
I applied via Approached by Company and was interviewed in Mar 2023. There were 3 interview rounds.
Develop an ML solution from the given problem statement and data.
(3 Questions)
- Q1. Discussion on your assignment and previous work.
- Q2. Why did you choose the model?
- Q3. Explain how GBM works
- Ans.
GBM is a machine learning algorithm that builds multiple decision trees to predict outcomes and combines them to improve accuracy.
GBM stands for Gradient Boosting Machine
It builds multiple decision trees sequentially, each one correcting errors made by the previous tree
The final prediction is a combination of predictions from all the trees
GBM is an ensemble learning technique that is popular for its high accuracy and f
Interview Preparation Tips
Skills evaluated in this interview
I applied via LinkedIn and was interviewed in Aug 2022. There were 5 interview rounds.
(1 Question)
- Q1. General resume based question. Interviewer asked me to explain one of the past project and asked some questions based on that
It was the assignment including the data science problem and SQL questions for one of the datetime table. Assignment was for 3 hours and had to complete some mandatory questions from data science assignment.
(1 Question)
- Q1. It was a technical + data science case study round. Interviewer asked me some technical questions based on machine learning and gave me one case study.
(1 Question)
- Q1. Interviewer asked me some general behavioural questions and also gave me one case study to solve.
Interview Preparation Tips
(1 Question)
- Q1. How to check model performance? Over fit vs underfit?
- Ans.
Model performance can be checked using various metrics such as accuracy, precision, recall, F1 score, and confusion matrix.
Split data into training and testing sets
Train the model on the training set
Evaluate the model on the testing set using metrics such as accuracy, precision, recall, F1 score, and confusion matrix
If the model performs well on the testing set, it is not overfit or underfit
If the model performs well o...
Python code for 45 mins. Pandas , group by , filtering questions
(1 Question)
- Q1. Mostly behavioral questions
Interview Preparation Tips
Skills evaluated in this interview
Yash Sinha
Selected
I applied via Recruitment Consulltant and was interviewed before Apr 2022. There were 4 interview rounds.
It had done sql tests
(1 Question)
- Q1. Case study regarding a business use case
(1 Question)
- Q1. Technical interview with sql & ML
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