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Roadzen Senior Data Scientist Interview Questions and Answers
Roadzen Senior Data Scientist Interview Experiences
1 interview found
Shobhit Maheshwari
Selected
I applied via Instahyre and was interviewed before Dec 2023. There was 1 interview round.
(2 Questions)
- Q1. Optimisers and their usage
- Ans.
Optimisers are algorithms used to minimize or maximize an objective function.
Optimisers are used in machine learning to find the best parameters for a model.
Common optimisers include Gradient Descent, Adam, RMSprop, and Adagrad.
The choice of optimiser can impact the training speed and performance of a model.
Hyperparameter tuning may involve selecting the best optimiser for a specific task.
- Q2. Data Sparsity handling
Interview Preparation Tips
Top trending discussions
Interview questions from similar companies
Anonymous
Python programming,SQL question
(2 Questions)
- Q1. Asked some puzzle questions
- Q2. Asked one leetcode easy question. 3 sum
Kunjika Bisht
DSA question, probability, statistical test
I applied via LinkedIn and was interviewed in May 2021. There were 4 interview rounds.
Interview Questionnaire
6 Questions
- Q1. Machine Learning questions, graphs were not asked
- Q2. Deep Learning
- Q3. Machine Learning
- Q4. Core ML Principle, CV
- Q5. MLP
- Q6. Recommendation Systems
Interview Preparation Tips
Round type - Coding
Round duration - 45mins
Round description - Coding question were askedRound 2
Round type - Machine Learning
Round duration - 45minsRound 3
Round type - TechnicalShareChat interview Preparation:What resources did you refer to prepare for the interview? - As many books/resources on the internet because the topic is very vast. Do not refer to only one resource.What tips would you give to other job seekers? - Machine Learning matters a lot here, coding is very easy. You have to be well versed with ML. ML round of ShareChat was the most difficult round I have encountered.What was the final outcome of your interview?Selected
(2 Questions)
- Q1. Tell me about your projects?
- Q2. How do you approach the project if you are using logistic regression model?
- Ans.
Approach involves data preprocessing, model training, evaluation, and interpretation.
Perform data preprocessing such as handling missing values, encoding categorical variables, and scaling features.
Split the data into training and testing sets.
Train the logistic regression model on the training data.
Evaluate the model using metrics like accuracy, precision, recall, and F1 score.
Interpret the model coefficients to under...
(2 Questions)
- Q1. What are you future goals?
- Q2. What would you do if your interested field doesnt have any work in the company?
- Ans.
I would seek opportunities to apply my skills in related fields within the company.
Explore other departments or teams within the company that may have projects related to my field of interest
Offer to collaborate with colleagues in different departments to bring a new perspective to their projects
Seek out professional development opportunities to expand my skills and knowledge in related areas
Skills evaluated in this interview
I applied via Approached by Company and was interviewed in Aug 2024. There was 1 interview round.
(2 Questions)
- Q1. General ml questions
- Q2. Coding on dataframe from kaggle
(2 Questions)
- Q1. Basic Recommendation System Questions
- Q2. A B Testing Questions
Eash Sharma
(2 Questions)
- Q1. Design a recommendation system
- Ans.
Designing a recommendation system involves creating algorithms to suggest items to users based on their preferences and behavior.
Collect user data such as past purchases, ratings, and browsing history
Use collaborative filtering or content-based filtering techniques to make recommendations
Implement machine learning models like matrix factorization or neural networks for personalized recommendations
Evaluate the system's ...
- Q2. ML theoretical questions
(2 Questions)
- Q1. ML coding round
- Q2. Project discussion
Skills evaluated in this interview
I applied via Company Website and was interviewed in Dec 2024. There was 1 interview round.
Easy topics arrays, sequence sum.
I applied via LinkedIn and was interviewed in May 2021. There were 4 interview rounds.
Interview Questionnaire
6 Questions
- Q1. Machine Learning questions, graphs were not asked
- Q2. Deep Learning
- Q3. Machine Learning
- Q4. Core ML Principle, CV
- Q5. MLP
- Q6. Recommendation Systems
Interview Preparation Tips
Round type - Coding
Round duration - 45mins
Round description - Coding question were askedRound 2
Round type - Machine Learning
Round duration - 45minsRound 3
Round type - TechnicalShareChat interview Preparation:What resources did you refer to prepare for the interview? - As many books/resources on the internet because the topic is very vast. Do not refer to only one resource.What tips would you give to other job seekers? - Machine Learning matters a lot here, coding is very easy. You have to be well versed with ML. ML round of ShareChat was the most difficult round I have encountered.What was the final outcome of your interview?Selected
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