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Optum Senior Data Scientist Interview Questions and Answers
Optum Senior Data Scientist Interview Experiences
1 interview found
Yogesh Jaiswal
(2 Questions)
- Q1. What is random forest
- Ans.
Random forest is an ensemble learning method used for classification and regression tasks.
Random forest is a collection of decision trees that are trained on random subsets of the data.
Each tree in the random forest independently predicts the target variable, and the final prediction is made by averaging the predictions of all trees.
Random forest is robust to overfitting and noisy data, and it can handle large datasets...
- Q2. Bias variance trade off
Skills evaluated in this interview
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Anonymous
I applied via Recruitment Consulltant and was interviewed in Sep 2022. There were 4 interview rounds.
(2 Questions)
- Q1. Random forest splitting mechanisms details
- Ans.
Random forest uses decision trees to split data into subsets based on feature importance.
Random forest builds multiple decision trees and selects the best split based on feature importance.
Each decision tree splits data into subsets based on a randomly selected subset of features.
The best split is determined by minimizing impurity or maximizing information gain.
Random forest can handle missing values and outliers.
Rando...
- Q2. ResNet architecture and skip connection related questions
(2 Questions)
- Q1. OCR related bounding box detection from image
- Q2. Deep learning based questions and details
(2 Questions)
- Q1. Salary discussion, current salary and expected
- Q2. About Optum, why you want to join
Interview Preparation Tips
Skills evaluated in this interview
Selected
I applied via Company Website and was interviewed in Sep 2024. There was 1 interview round.
(2 Questions)
- Q1. Basic ML with project experience
- Q2. Statistics and Python coding
Basic quant and apt questions
Run a model of ML or Dl
(1 Question)
- Q1. Check your interpersonal skills
I applied via Recruitment Consulltant and was interviewed in Sep 2022. There were 4 interview rounds.
(2 Questions)
- Q1. Random forest splitting mechanisms details
- Ans.
Random forest uses decision trees to split data into subsets based on feature importance.
Random forest builds multiple decision trees and selects the best split based on feature importance.
Each decision tree splits data into subsets based on a randomly selected subset of features.
The best split is determined by minimizing impurity or maximizing information gain.
Random forest can handle missing values and outliers.
Rando...
- Q2. ResNet architecture and skip connection related questions
(2 Questions)
- Q1. OCR related bounding box detection from image
- Q2. Deep learning based questions and details
(2 Questions)
- Q1. Salary discussion, current salary and expected
- Q2. About Optum, why you want to join
Interview Preparation Tips
Skills evaluated in this interview
I applied via Naukri.com and was interviewed before Oct 2020. There were 3 interview rounds.
Interview Questionnaire
1 Question
- Q1. 1) Model building process of one of my previous projects 2) Random forest hyperparameters 3) ROC curve, using the ROC curve to set probability cutoffs in classication models 4) Gradient boosting techniques...
- Ans.
Data Scientist interview questions on model building, random forest, ROC curve, gradient boosting, and real estate valuation
For model building, I followed the CRISP-DM process and used various algorithms like logistic regression, decision trees, and random forest
Random forest hyperparameters include number of trees, maximum depth, minimum samples split, and minimum samples leaf
ROC curve is a graphical representation of...
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