Data Science Interview Preparation

Data Science Interview Tips: Statistics, SQL, and ML

Data science interviews uniquely combine statistics, SQL, programming (Python/R), and business acumen. The typical loop includes: SQL assessment, statistics/probability, ML knowledge, coding, and a case study/presentation. According to Indeed, the average data scientist salary in 2026 is $135K-$185K.

The top 3 skills tested in data science interviews: SQL (100% of interviews), probability/statistics (85%), and business case analysis (75%). Technical ML knowledge matters, but data fundamentals matter more.

Data Science Interview Rounds

• SQL — Window functions, CTEs, self-joins, aggregation. See SQL interview questions
• Statistics — Hypothesis testing, p-values, confidence intervals, A/B test design
• ML — Model selection, feature engineering, evaluation metrics (precision, recall, F1, AUC)
• Coding — Python/Pandas data manipulation, visualization
• Case Study — Business problem → data analysis → recommendations

Related: ML interview guide, Python interview questions.