Comparison
DataScienceHired vs StrataScratch
Both platforms help you practice data science interview questions in your browser. Here's an honest look at where each one is stronger — including where we're not.
| DataScienceHired | StrataScratch | |
|---|---|---|
| Monthly price | $20/month — everything included | $34–49/month across three tiers |
| Lifetime access | $99 launch price (list $199) | $289 one-time |
| Free trial | 30 days of full Pro — no card required | No trial; limited free tier |
| Money-back guarantee | 7 days | 5 days |
| Question bank | 403+ questions (40 free) | 1,000+ questions |
| Modern ML & AI coverage | 140+ concept questions on LLMs, neural networks, NLP, PyTorch/TensorFlow | Primarily SQL/Python coding questions |
| In-browser code execution | Yes — SQL and Python, no signup needed to try | Yes |
| Data projects & notebooks | No | 50+ projects, hosted notebooks (higher tiers) |
| AI mock interviews | 10/month at $20 (trial includes 1) | 5–10/month at $34–44; unlimited at $49 |
| 1:1 human coaching | Yes — founder-led sessions & mock interviews | No |
StrataScratch pricing and features as of July 2026, from their public pricing page. Check stratascratch.com for current details.
Choose StrataScratch if…
- → You want the largest possible bank of SQL coding questions and don't mind paying $34+/month for it.
- → You want data projects, hosted notebooks, and portfolio hosting alongside interview prep.
- → AI mock interviews matter more to you than price.
Choose DataScienceHired if…
- → You want to try the full product for 30 days before paying anything.
- → Your interviews cover modern ML — LLMs, transformers, neural networks — not just SQL.
- → You want one simple price ($20/month or $99 once) instead of a three-tier feature matrix.
- → You want the option of real human coaching from the person who built the platform.
Try the whole platform free for 30 days
Every signup gets full Pro access for 30 days — all 403+ questions, solutions, and explanations. No card required. If it's not for you, you've lost nothing.