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You don’t need to be a LeetCode grandmaster.
But data science interviews still test your problem-solving mindset—and these 5 types of challenges are the ones that actually matter.

Here’s what to focus on (with examples) 👇

🔹 1. String Manipulation (Common in Data Cleaning)

✅ Parse messy columns (e.g., split “Name_Age_City”)
✅ Regex to extract phone numbers, emails, URLs
✅ Remove stopwords or HTML tags in text data

Example: Clean up a scraped dataset from LinkedIn bias

🔹 2. GroupBy and Aggregation with Pandas

✅ Group sales data by product/region
✅ Calculate avg, sum, count using .groupby()
✅ Handle missing values smartly

Example: “What’s the top-selling product in each region?”

🔹 3. SQL Join + Window Functions

✅ INNER JOIN, LEFT JOIN to merge tables
✅ ROW_NUMBER(), RANK(), LEAD(), LAG() for trends
✅ Use CTEs to break complex queries

Example: “Get 2nd highest salary in each department”

🔹 4. Data Structures: Lists, Dicts, Sets in Python

✅ Use dictionaries to map, filter, and count
✅ Remove duplicates with sets
✅ List comprehensions for clean solutions

Example: “Count frequency of hashtags in tweets”

🔹 5. Basic Algorithms (Not DP or Graphs)

✅ Sliding window for moving averages
✅ Two pointers for duplicate detection
✅ Binary search in sorted arrays

Example: “Detect if a pair of values sum to 100”

🎯 Tip: Practice challenges that feel like real-world data work, not textbook CS exams.

Use platforms like:

StrataScratch
Hackerrank (SQL + Python)
Kaggle Code

I have curated the best interview resources to crack Data Science Interviews
👇👇
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📊Here's a breakdown of SQL interview questions covering various topics:

🔺Basic SQL Concepts:
-Differentiate between SQL and NoSQL databases.
-List common data types in SQL.

🔺Querying:
-Retrieve all records from a table named "Customers."
-Contrast SELECT and SELECT DISTINCT.
-Explain the purpose of the WHERE clause.


🔺Joins:
-Describe types of joins (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN).
-Retrieve data from two tables using INNER JOIN.

🔺Aggregate Functions:
-Define aggregate functions and name a few.
-Calculate average, sum, and count of a column in SQL.

🔺Grouping and Filtering:
-Explain the GROUP BY clause and its use.
-Filter SQL query results using the HAVING clause.

🔺Subqueries:
-Define a subquery and provide an example.

🔺Indexes and Optimization:
-Discuss the importance of indexes in a database.
&Optimize a slow-running SQL query.

🔺Normalization and Data Integrity:
-Define database normalization and its significance.
-Enforce data integrity in a SQL database.

🔺Transactions:
-Define a SQL transaction and its purpose.
-Explain ACID properties in database transactions.

🔺Views and Stored Procedures:
-Define a database view and its use.
-Distinguish a stored procedure from a regular SQL query.

🔺Advanced SQL:
-Write a recursive SQL query and explain its use.
-Explain window functions in SQL.

✅👀These questions offer a comprehensive assessment of SQL knowledge, ranging from basics to advanced concepts.

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