AmbitionBox
Interview Questions
- Reviews
- Salaries
- Interview Questions
- About Company
- Benefits
- Jobs
- Office Photos
- Community
Add office photos
i
Optum Global Solutions
CompareProud winner of ABECA 2024 - AmbitionBox Employee Choice Awards
Filter interviews by
Optum Global Solutions Data Scientist Interview Questions and Answers
Optum Global Solutions Data Scientist Interview Experiences
9 interviews found
Anonymous
I applied via Campus Placement
Bulb and switch puzzle
Rope burning and length question
(1 Question)
- Q1. Why you want to join optum
(1 Question)
- Q1. Fundamentals of ML, classical ML
- Ans.
Fundamentals of classical machine learning
Classical machine learning involves algorithms that learn from data and make predictions or decisions.
Common algorithms include linear regression, decision trees, support vector machines, and k-nearest neighbors.
Key concepts include training data, testing data, model evaluation, and hyperparameter tuning.
Classical ML is often used for tasks like classification, regression, clus
(1 Question)
- Q1. Research paper discussion
Skills evaluated in this interview
Selected
I applied via Referral and was interviewed before Jul 2023. There were 3 interview rounds.
Hacker rank coding questions
(2 Questions)
- Q1. Python list dictionary
- Q2. Projects related questions which I have done earlier
(2 Questions)
- Q1. Why you want to join
- Q2. About my projects
Interview Preparation Tips
What people are saying about Optum Global Solutions
Selected
I applied via campus placement at Indian Institute of Technology (IIT), Kanpur and was interviewed before Jul 2023. There were 3 interview rounds.
Puzzlee on three bulb, switched off, tell which one
(2 Questions)
- Q1. Puzzle - rope burn and length
- Q2. Strength and weakness
Optum Global Solutions interview questions for designations
Prayank Kulshrestha
I applied via Naukri.com and was interviewed in Mar 2022. There were 2 interview rounds.
(2 Questions)
- Q1. Question on NER models
- Q2. Question from project
(2 Questions)
- Q1. Critical thinking questions
- Q2. Case studies based questions
Interview Preparation Tips
Selected
I applied via Referral and was interviewed before Aug 2022. There were 4 interview rounds.
(1 Question)
- Q1. Question related to CNN in details, Different ML algorithms, Questions related to pandas
(1 Question)
- Q1. Question related to MLOps, GitHub
(1 Question)
- Q1. Salary expectations
Interview Preparation Tips
Interview Questionnaire
1 Question
- Q1. Good knowledge about Machine Learning algorithms and their mathematical structure.
Interview Preparation Tips
I applied via Recruitment Consultant and was interviewed in Mar 2021. There were 3 interview rounds.
Interview Questionnaire
2 Questions
- Q1. Super Quick Case Study on Sales
- Q2. Questions on Machine learning Projects in your Resume
Interview Preparation Tips
Other topics: SQL, Excel, Pivot tables
I was interviewed before Jul 2021.
(2 Questions)
- Q1. Model evaluation and performance metrices
- Q2. Explaination of bagging and boosting techniques
- Ans.
Bagging and boosting are ensemble techniques used to improve the accuracy of machine learning models.
Bagging involves training multiple models on different subsets of the training data and then combining their predictions through voting or averaging.
Boosting involves iteratively training models on the same data, with each subsequent model focusing on the samples that the previous models misclassified.
Bagging reduces va...
Interview Preparation Tips
Skills evaluated in this interview
Interview questions from similar companies
(3 Questions)
- Q1. Difference between bagging and boosting
- Ans.
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.
Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.
Boosting involves training multiple models sequentially, where each subsequent model c...
- Q2. Parameters of Decision Tree
- Ans.
Parameters of a Decision Tree include max depth, min samples split, criterion, and splitter.
Max depth: maximum depth of the tree
Min samples split: minimum number of samples required to split an internal node
Criterion: function to measure the quality of a split (e.g. 'gini' or 'entropy')
Splitter: strategy used to choose the split at each node (e.g. 'best' or 'random')
- Q3. Explain any one of your project in detail
- Ans.
Developed a predictive model to forecast customer churn in a telecom company
Collected and cleaned customer data including usage patterns and demographics
Used machine learning algorithms such as logistic regression and random forest to build the model
Evaluated model performance using metrics like accuracy, precision, and recall
Provided actionable insights to the company to reduce customer churn rate
Skills evaluated in this interview
Optum Global Solutions Interview FAQs
Tell us how to improve this page.
Optum Global Solutions Interviews By Designations
- Optum Global Solutions Claims Associate Interview Questions
- Optum Global Solutions Software Engineer Interview Questions
- Optum Global Solutions Medical Coder Interview Questions
- Optum Global Solutions Clinical Investigator Interview Questions
- Optum Global Solutions Software Developer Interview Questions
- Optum Global Solutions Senior Software Engineer Interview Questions
- Optum Global Solutions Associate Software Engineer Interview Questions
- Optum Global Solutions Data Analyst Interview Questions
- Show more
Interview Questions for Popular Designations
- Senior Data Scientist Interview Questions
- Jr. Data Scientist Interview Questions
- Decision Scientist Interview Questions
- Associate Data Scientist Interview Questions
- Data Scientist Intern Interview Questions
- Lead Data Scientist Interview Questions
- Trainee Decision Scientist Interview Questions
- Research Scientist Interview Questions
- Show more
Optum Global Solutions Data Scientist Interview Process
based on 7 interviews
2 Interview rounds
- Resume Shortlist Round
- HR Round
Data Scientist Interview Questions from Similar Companies
Fast track your campus placements
Optum Global Solutions Data Scientist Reviews and Ratings
based on 41 reviews
Rating in categories
|
Claims Associate
4.3k
salaries
|  ₹1.5 L/yr - ₹6 L/yr |
|
Senior Software Engineer
2.8k
salaries
| ₹9.7 L/yr - ₹33 L/yr |
|
Software Engineer
2.6k
salaries
| ₹6.2 L/yr - ₹22 L/yr |
|
Medical Coder
1.2k
salaries
| ₹1.5 L/yr - ₹8 L/yr |
|
Senior Claims Associate
1.2k
salaries
| ₹2.1 L/yr - ₹6.3 L/yr |
Cognizant
Accenture
IBM
TCS
- Home >
- Interviews >
- Optum Global Solutions Interview Questions >
- Optum Global Solutions Data Scientist Interview Questions
