WESCO Lead Data Scientist Interview Questions and Answers

Q1. Tell me about your projects?
Add your answer
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...read more
Answered by AI
Add your answer

Q1. What are you future goals?
Add your answer
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
Answered by AI
Add your answer

Q1. Breadth of data science, Linear algebra, prob&stats, Lin reg, Log reg, DT, RF
Add your answer

Q1. Grilled in Mathematics behind Lin Reg, closed form solution, scalebility of lin reg
Add your answer

Q1. System design, took a project from my resume and asked me to design the whole solution. Project was a chatbot
Add your answer

Easy topics arrays, sequence sum.

1.Describe your project.
2.Explain machine learning concept.

Presentation based question on case study

Q1. Tell something which you haven't put in your resume
Ans. 
I have experience in organizing and leading community service projects
• Organized a charity event to raise funds for a local animal shelter

• Led a team of volunteers in cleaning up a park in the neighborhood

• Coordinated a food drive for a homeless shelter
Answered by AI
Add your answer

Q1. How do you define model Gini?
Ans. 
Model Gini is a measure of statistical dispersion used to evaluate the performance of classification models.
• Model Gini is calculated as twice the area between the ROC curve and the diagonal line (random model).

• It ranges from 0 (worst model) to 1 (best model), with higher values indicating better model performance.

• A Gini coefficient of 0.5 indicates a model that is no better than random guessing.

• Commonly used in credit
Answered by AI
Add your answer
Q2. How to you train XG boost model
Ans. 
XGBoost model is trained by specifying parameters, splitting data into training and validation sets, fitting the model, and tuning hyperparameters.
• Specify parameters for XGBoost model such as learning rate, max depth, and number of trees

• Split data into training and validation sets using train_test_split function

• Fit the XGBoost model on training data using fit method

• Tune hyperparameters using techniques like grid search
Answered by AI
Add your answer

5 dsa questions and 5 aptitude questions given. DSA were of medium to hard based on dp

Questions related to basic coding were asked, and some background on projects and discussions alongside maths and statistics concepts

Q1. Questions related to projects done at my previous company
Add your answer

Q1. Questions related to my work at previous company
Add your answer
Q2. ML system design use case type of discussion
Add your answer

About the new technologies

Array questions and