Great it was a great interview with questions being asked about my experience and how it applies to CGI. Just answer according to your experience and everything will work out great,

a. Statistics & Probability Hypothesis testing, p-values, confidence intervals Descriptive stats: mean, median, mode, variance, skewness, kurtosis Probability distributions: Normal, Poisson, Binomial Bayes’ Theorem and conditional probabilities b. Machine Learning Supervised vs. unsupervised learning Model evaluation metrics (e.g. precision, recall, AUC-ROC, confusion matrix) Algorithms: linear/logistic regression, decision trees, random forest, SVM, k-NN, clustering (K-means, DBSCAN), PCA Bias-variance trade-off, overfitting/underfitting, cross-validation c. Deep Learning (if relevant) Neural network basics (activation functions, backpropagation) CNNs, RNNs/LSTMs for NLP or image data (if role-specific) Frameworks: TensorFlow, PyTorch d. Coding & Data Manipulation Python (pandas, NumPy, scikit-learn, matplotlib/seaborn) SQL: Joins, subqueries, window functions, CTEs