Data science interviews are unlike any other technical interview. You need to move fluently between statistical theory, ML system design, and business impact — often within the same question. A case about a recommendation engine might test your understanding of feature drift, your experiment design instincts, and your ability to frame the business tradeoffs of a model serving decision, all in 45 minutes.
Data Science Interview gives you that practice. Our AI coach challenges you with realistic data science cases — from diagnosing A/B test anomalies across segments to debugging ML model degradation in production — and gives you structured feedback on your statistical reasoning, diagnostic frameworks, and the precision of your quantitative claims.
How it works
- Practice data science cases modeled on real interview questions from Two Sigma, Palantir, DoorDash, and Citadel
- Get AI-powered feedback on your experiment design, ML pipeline diagnostics, and metric decomposition
- Build skills across statistical inference, model evaluation, feature engineering, and causal reasoning
- Track your progress across 20+ data science competencies with adaptive difficulty
Why data science interviews need dedicated prep
Data science interviewers are looking for candidates who can think both as scientists and as engineers. Generic SQL or coding prep does not develop the multi-layer reasoning that top firms like Palantir and Two Sigma evaluate — the ability to trace a business metric decline through data pipeline issues, feature drift, model degradation, and serving infrastructure problems all at once.
Our AI does not accept imprecise answers. It pushes you to state your hypotheses with testable predictions, specify the statistical tests you would run and why, quantify the expected effect sizes, and articulate the business impact of your recommendations — exactly the bar that data science hiring panels set.
Built for aspiring data scientists and ML engineers
Whether you are targeting your first data scientist role at a high-growth startup, aiming for a quantitative research position at a hedge fund like Citadel or Two Sigma, or preparing for a senior applied science role at a marketplace like DoorDash, Data Science Interview builds the diagnostic and experimental reasoning skills that compound throughout your career.