Voleon Data Scientist Interview Experience — Python File Handling Before an Open-Ended Regression Task

Question format

The interviewer gives one or more datasets:

X: contains multiple features, possibly an m x n matrix
y: a continuous, real-valued target

You're expected to explore:

• which columns are related to y
• which features provide useful signal
• whether there's redundant information or collinearity among the features
• how you should build and evaluate a predictive model

Before that part, there were also 3 very simple questions that were more about basic engineering skills, mainly testing Python file handling rather than LeetCode-style algorithms.

1. Basic file operations

May involve:

• opening, reading, and writing files
• iterating over files in a directory
• checking whether a file or directory exists
• joining and manipulating file paths
• creating output files or directories

2. Rename filenames

The question might ask you to batch-rename files according to some rule, for example:

• adding a prefix or suffix
• replacing a certain string in the filename
• changing the numbering format
• keeping the original extension
• renaming all files in a directory that match certain conditions

3. Log cleaning / keyword filtering

Given a log file, read it line by line and clean it based on keywords.

Possible task forms include:

• keeping only lines that contain certain keywords
• removing lines that contain certain keywords
• extracting a specific type of log entry
• removing empty or invalid lines
• stripping, splitting, or reformatting each line
• writing the cleaned result to a new file