Hi Everyone,
I am preparing for an online QuantHub assessment for a Data Science Analyst role at McKinsey. The assessment has the following modules: Storytelling with Data, Analyst, and SQL.
Do you all have any tips/advice for preparing? I have completed the practice tests for the following: SQL, Wrangling, Storing, and Exploration. Any additional insight / resources would be extremely helpful.
Thanks!
(editiert)
Hello!
Unfortunately no, although I have looked for examples in several occasions and haven´t found them. It´s still really niche :(
Good luck!
Cheers,
Clara
For storytelling you should read Barbara's Minto book which is Mckinsey's bible on communication: The Pyramid Principle
Based on what you described in your comment this is exactly what they are looking for.
(editiert)
Congrats what about the other questions related to Python , R and stat . Which resources I can used to practice and what are the practice tests . I am kinda new to Data Science .
No worries! I completely understand. I actually ended up taking the assessment and passed! For future awareness / for anyone who was wondering, here’s my personal recommendation: 1. SQL: practice easy / medium questions on Leetcode and Hackerrank 2. Analyst (Data Wrangling, Exploring, Storing): Understand data architecture / warehouse / Snowflake principles (i.e. asynchronous replication, load balancers, etc.). Also, practicing SQL was helpful here (some questions around ‘which one of these queries would lead to an error?’) 3. Data Storytelling: Just understand key principles in data visualization (i.e. know when to use certain graphs, etc.) and interpreting graphs
(editiert)