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GeoIQ Data Scientist Interview Questions and Answers
GeoIQ Data Scientist Interview Experiences
2 interviews found
Anonymous
I applied via Recruitment Consulltant and was interviewed in Jan 2024. There was 1 interview round.
(1 Question)
- Q1. 1 round was technically discussion based on python and the projects you worked on. Dataset was given and asked to perform some operations using pandas like using group , count and nunique
I applied via Naukri.com and was interviewed in Mar 2024. There was 1 interview round.
(2 Questions)
- Q1. Explain end to end project
- Ans.
End to end project involves all stages of a project from data collection to deployment.
Start with defining the problem and objectives
Collect and preprocess data
Perform exploratory data analysis and feature engineering
Build and train machine learning models
Evaluate model performance and fine-tune
Deploy the model and monitor its performance
- Q2. What left skewed and right skewed data. And how to treat them
- Ans.
Left skewed data has a long tail on the left side, while right skewed data has a long tail on the right side.
Left skewed data: mean < median < mode. Example: income distribution in a developing country.
Right skewed data: mean > median > mode. Example: age distribution in a population.
Treatment: For left skewed data, consider log transformation. For right skewed data, consider square root transformation.
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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
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
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)
Case study design oka6y
(2 Questions)
- Q1. Case study explain
- Q2. Ml concept advance
vishal sharma
Python coding 45 mins
(2 Questions)
- Q1. Fraud data balancing
- Q2. Recommendation metrics
(2 Questions)
- Q1. Why join Turing?
- Q2. Ability to learn new skills
Simple mediam DSA style questions around ML
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