Quant Interview Data Final Drill
Final quant data drill for interviews covering point-in-time data, joins, corporate actions, alternative data, SQL checks, and cleaning risk.
Candidates preparing for quant research, data, and developer interview data prompts.
Protect point-in-time logic
Every dataset should be checked for when each value became known. A feature that uses later corrections or future membership can invalidate research.
Treat joins as risk points
Identifiers, dates, time zones, survivorship, and many-to-many joins can silently change results. Explain how you would test row counts and unmatched records.
Adjust corporate actions carefully
Splits, dividends, delistings, and symbol changes affect prices and returns. State whether data is raw, adjusted, and available at the decision time.
Use SQL checks as evidence
Simple checks for nulls, duplicates, ranges, timestamp ordering, and referential integrity can reveal data problems before modeling begins.
Common mistakes
Candidates often assume cleaned data is correct. Strong data answers discuss timing, lineage, validation checks, and how errors could affect conclusions.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.