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      Canadian Tire

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      Senior Data Scientist Interview

      30 Apr 2020
      Anonymous interview candidate
      No offer
      Positive experience
      Difficult interview

      Application

      I applied online. I interviewed at Canadian Tire

      Interview

      Very thorough interview process. Good experience overall. A series of questions with the VP of Analytics. The interview started out with a series of general quesitons about management style. It then moved on to personality-type questions.

      Interview questions [1]

      Question 1

      How have you dealt with stressful situations on the job in the past?
      1 Answer

      Other Senior Data Scientist interview reviews for Canadian Tire

      Senior Data Scientist Interview

      4 June 2026
      Anonymous employee
      Toronto, ON
      Accepted offer
      Positive experience
      Average interview

      Application

      I applied in-person. I interviewed at Canadian Tire (Toronto, ON) in June 2026

      Interview

      First, they ask whether you are comfortable working in the office five days a week, as the position requires regular on-site attendance. After that, candidates complete a 50-minute written assessment focused on Machine Learning, Mathematics, and Statistics. The assessment evaluates your understanding of core concepts, problem-solving abilities, and analytical thinking rather than coding skills. It may include questions on probability, hypothesis testing, regression, model evaluation, machine learning algorithms, and other data science fundamentals.

      Interview questions [1]

      Question 1

      Statistics Probability and conditional probability Hypothesis testing p-values and confidence intervals Bias and variance Sampling methods A/B testing Regression interpretation Machine Learning Supervised vs. unsupervised learning Linear and logistic regression Decision trees and random forests Gradient boosting (e.g., XGBoost) Cross-validation Overfitting and regularization Evaluation metrics: Accuracy Precision Recall F1-score ROC-AUC Math Basic calculus concepts (derivatives and optimization) Matrix algebra Linear algebra fundamentals Expected value and variance Bayes' theorem Optimization concepts used in machine learning
      Answer question