Listen to this Post
You Should Know:
To maximize your Data Science interview preparation, follow this 7-day plan with Claude AI, incorporating practical coding, SQL, and research techniques. Below are verified commands, scripts, and steps to streamline your prep.
Day -7: Research the Company
Use Claude 4’s Research Mode to scrape earnings calls, competitor data, and product updates.
Linux Command to Scrape Earnings Calls (using `curl` and jq):
curl -s "https://api.company.com/earnings" | jq '.transcripts[] | select(.quarter == "Q2-2025")' > earnings_analysis.json
Day -6: Learn Company Metrics & SQL Practice
Generate mock datasets using Claude and practice SQL queries.
SQL Practice (PostgreSQL):
-- Generate metrics from mock data SELECT product_id, COUNT(user_id) AS active_users, SUM(revenue) AS total_revenue FROM company_metrics GROUP BY product_id ORDER BY total_revenue DESC;
Day -5: Case Study Mock Interviews
Simulate case studies with Claude’s Extended Thinking Mode. Use Python for data analysis:
Python Script for Metric Tradeoffs:
import pandas as pd
data = pd.read_csv("mock_metrics.csv")
correlation = data[['user_growth', 'revenue']].corr()
print(correlation)
Day -4: DS&A Interview Simulation
Run algorithm challenges. Example Linux command for timing code execution:
time python3 binary_search.py Measure efficiency
Day -3: SQL Mock Interviews
Optimize queries. Check for missing indexes:
EXPLAIN ANALYZE SELECT FROM large_table WHERE user_id = 1000;
Day -2: More Case Studies
Reuse Day -5 methods with new datasets.
Day -1: Behavioral Interview Polish
Use Claude’s web search to extract success traits. Store notes in a file:
echo "Key traits: adaptability, data-driven storytelling" >> interview_notes.txt
Day of Interview
Summarize prep with Claude’s context recall.
What Undercode Say:
This plan merges AI-powered research with hands-on coding/SQL drills. Automation (e.g., curl, jq) and optimization (EXPLAIN ANALYZE) are critical for real-world Data Science.
Prediction:
AI tools like Claude will dominate interview prep, reducing research time by 70% while increasing SQL/coding accuracy.
Expected Output:
- Structured 7-day prep.
- SQL/Python scripts for metrics.
- Automated data scraping commands.
URLs:
IT/Security Reporter URL:
Reported By: Data Dawn – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
