•1 min read•from Data Science
Leetcode to move to AI roles
Our take
Transitioning from a data scientist role in a FAANG company to an AI-focused position can be a strategic move, especially given the significant compensation differences that can reach up to $200,000. However, the path is often obstructed by challenging LeetCode interview rounds, particularly with tricky topics like dynamic programming. As data science becomes increasingly specialized and the demand for AI expertise grows, many are questioning whether it's time to embrace this shift. Has anyone successfully made this transition? Your insights could be invaluable.
I work as a DS in a faang. In Faangs, the DS are siloed off to an extent and the machine learning work is done by applied scientists or MLE software engineers. The entry to such roles in Faangs is gatekept by leetcode rounds in interviews. Leetcode seems daunting, ngl. Especially topics like DP. Anyone made the switch? Feels like it is worth it sometimes because the comp difference is easily 150-200k more.
Edit: I also feel like with the push for AI, DS is getting more and more narrow. It makes sense to switch.
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#machine learning in spreadsheet applications#rows.com#natural language processing for spreadsheets#generative AI for data analysis#digital transformation in spreadsheet software#Excel alternatives for data analysis#financial modeling with spreadsheets#DS (Data Science)#Leetcode#machine learning#AI roles#MLE (Machine Learning Engineer)#push for AI#Faang#interviews#DP (Dynamic Programming)#switch#applied scientists#compensation#software engineers