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10times Data Scientist Interview Questions and Answers
10times Data Scientist Interview Experiences
1 interview found
Anonymous
Selected
I applied via Referral and was interviewed before Jun 2023. There was 1 interview round.
(2 Questions)
- Q1. Model evaluation methods to check model performance
- Ans.
Various model evaluation methods are used to check the performance of a data science model.
Cross-validation: splitting data into multiple subsets for training and testing
Confusion matrix: evaluating classification models based on true positives, true negatives, false positives, and false negatives
ROC curve: plotting the true positive rate against the false positive rate
Precision, recall, and F1 score: metrics for evalu...
- Q2. Projects done so far with tech explanation
- Ans.
I have worked on projects involving machine learning algorithms for predictive analytics and natural language processing.
Developed a predictive model using random forest algorithm to forecast customer churn in a telecom company.
Implemented sentiment analysis using natural language processing techniques to analyze customer reviews for a retail company.
Utilized deep learning techniques such as LSTM for time series foreca
Skills evaluated in this interview
Top trending discussions
Interview questions from similar companies
Anubhav Kesari
(3 Questions)
- Q1. Questions on Past Project
- Q2. SQL Dense Rank - also having the option to do in Pandas
- Q3. Pandas groupby on a dataset given - required to calculate group wise yoy rate of a column
(2 Questions)
- Q1. Past project ( which he chose , he chose my very first project , which I had forgotten) so ended up screwing it
- Q2. SQL / Pyspark question - difficult question
(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
(2 Questions)
- Q1. Basic Recommendation System Questions
- Q2. A B Testing Questions
I applied via Company Website and was interviewed in Dec 2024. There was 1 interview round.
Easy topics arrays, sequence sum.
Prasanna Pradhan
Build a simple cat and dog image classifier
(1 Question)
- Q1. ML related questions
(1 Question)
- Q1. Behavioural questions, basically to check if you will be fit in a team
Case study design oka6y
(2 Questions)
- Q1. Case study explain
- Q2. Ml concept advance
(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
(2 Questions)
- Q1. Basic Recommendation System Questions
- Q2. A B Testing Questions
Questions related to basic coding were asked, and some background on projects and discussions alongside maths and statistics concepts
(1 Question)
- Q1. Questions related to projects done at my previous company
(2 Questions)
- Q1. Questions related to my work at previous company
- Q2. ML system design use case type of discussion
Interview Preparation Tips
Also practice some level of basic PyTorch stuff and specially Bert architecture (in terms of code)
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