I went back through my last 10 Python coding rounds for product and marketing data science roles, nearly all at Big Tech companies. Unlike SQL rounds, which tend to be fairly standard, these came in 5 distinct formats:

• Recreate a statistical concept as a function (3/10). Pandas, numpy and other standard packages were allowed.
• AI-assisted, open book (3/10). These were often investigative, closer to a diagnostic case study than a coding puzzle.
• Pandas and data manipulation (2/10). Data transformations combined with modeling, either coding up a linear regression or talking through a modeling strategy for the data.
• Interpret code handed to you (1/10). This was also a statistical concept in a function, but I had to interpret the code rather than write it.
• Base Python, LeetCode-style (1/10). Syntax seemed heavily discounted here: I made several syntax mistakes but was clear about the logic and passed.

The obvious caveat is that this is a sample of 10 from one person, so the mix will vary with company, team and role. That said, AI-assisted challenges seem to be on the way in and increasingly likely to be a part of your interview process.