J'ai postulé en ligne. J'ai passé un entretien chez Expedia Group (Seattle, WA) en avr. 2026
Entretien
The role was a causal inference-heavy pricing role. Started with a HR phone screen followed by 4 interviews over two rounds.
The first technical round involved foundational causal inference theory questions followed by a pair programming component that involved refactoring ML model code.
The final round consisted of 3 interviews that involved classical ML theory, a case study and behavioural questions respectively.
The entire process took nearly 6 weeks. I was strung along for a few weeks after the final round by HR before I ultimately got a rejection.
Questions d'entretien [1]
Question 1
Explain how you would perform cross validation on time series data?
In what circumstances would you use ridge regression over lasso and vice versa?
How would you reduce the variance of the average causal effect estimate?
J'ai postulé via la recommandation d'un employé. Le processus a pris 4 semaines. J'ai passé un entretien chez Expedia Group (Seattle, WA) en juin 2024
Entretien
One Hr call, one call with the hiring manager, and then the final round consists of 4 interviews. Overall a good experience. The questions are wrt to the role. Questions go from behavioral to stats, data science to data manipulation and intuitions plus coding (python and SQL).