Creation of skip list: Las Vegas or Monte Carlo?
The difference between a Las Vegas algorithm and a Monte Carlo algorithm is that a Las Vegas algorithm is always correct but its running time may be large with small probability, whereas a Monte Carlo algorithm always has the same time complexity but may give wrong results with small probability.
These definitions are more appropriate for decision problems and optimization problems, and less for data structures. That said, they still make sense for data structures. Here are two examples:

Skip-lists correctly implement the list abstract data type. They are efficient with high probability. This is like a Las Vegas algorithm.
Bloom filters are always efficient (in this case we care about space complexity), but may give wrong results to queries. This is like a Monte Carlo algorithm.

Most data structures are designed with the Las Vegas objective in mind.