<aside> 💡 Pay for the premium version of interview prep websites like LeetCode. $30 a month subscription is totally worth it compared to the returns.

</aside>

Data Science interviews test many technical skills depending on the role or the level.

  1. Algorithmic coding
  2. SQL
  3. Data Coding
  4. Causal Inference
  5. Statistics
  6. Machine Learning

Algorithmic Coding Prep

  1. This is probably the most important component for software engineering roles, but not so much for data scientists. If you are interested in roles like Research Scientist, Research Data Scientist, then this will become important.

  2. One mistake people do here is spend too much time worrying about this and too much time to get good at this.

  3. Most interviews for data scientist roles will go into Arrays, but not so much into advanced concepts like binary trees. So spend most time in Easy and Medium Array questions.

    Preparation:

    1. All array questions could be categorized into 6-7 building blocks (eg: Two sum problems, Binary Search problems, Reverse traversal problems). If you are comfortable with those building blocks, you could code any array question by relating it to a building block and modifying the boiler plate code of that building block. Same goes for other concepts. This is the best way to prepare.
    2. Best place to learn building blocks is https://interviewcamp.io/
    3. Practice questions at https://leetcode.com/. Mostly go for easy and medium level array questions.
    4. A very good subset of coding questions https://www.teamblind.com/post/New-Year-Gift---Curated-List-of-Top-75-LeetCode-Questions-to-Save-Your-Time-OaM1orEU

SQL

  1. You cannot afford to bomb SQL rounds. So do well here.

    Preparation:

    1. https://mode.com/sql-tutorial/introduction-to-sql/ is the best place to brush up on SQL skills. Its concise and to the point

    2. https://selectstarsql.com/ seems like a great place to learn SQL.

    3. https://leetcode.com/problemset/all/?listId=5htp6xyg&page=1 has good practice questions.

    4. My mode SQL notes

      MODE SQL Notes