Me postulé en línea. El proceso tomó 1 semana. Acudí a una entrevista en PayPal en jul 2023
Entrevista
1 coding round followed by 2 technical rounds. coding round involved questions on data manipulation using SQL and python. technical rounds included past experience and ML depth and breadth. e.g. how does XGBoost classifier work, step by step.
Preguntas de entrevista [1]
Pregunta 1
SQL: joins, window functions python: new column assignment, string and list manipulations How does XGBoost work? step by step process with example How to represent categorical column with high cardinality How can embeddings be generated? How encoder-decoder might help in this How to find presence of multicollinearity in data? What is chi square test of independence? How to handle imbalanced classification? Why is PR auc better suited to such cases then ROC auc? How to handle large no. of classes in multiclass classification? What is negative sampling and how does it help in such scenarios?
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