AI has accelerated data scientists’ productivity, but its influence extends beyond speed. The technology is reshaping who owns data, how judgment is exercised, and the overall career trajectory of data scientists. These changes signal a broader transformation in the field’s structure and responsibilities.
By Yu Dong
The downside of conference travel The post Last Month’s Machine Learning Lessons Learned appeared first on Towards Data Science .
By Pascal Janetzky
Patience, Optimism, Discipline, Projects, Teams The post Lessons Learned After 8. 5 Years of ML appeared first on Towards Data Science .
By Pascal Janetzky
The article titled "The AI That Learned to Understand Long After It Stopped Trying" discusses a small, strange discovery in machine learning known as grokking. It highlights how this phenomenon involves an AI developing understanding after ceasing to actively try. The piece was originally published on Towards Data Science.
By Utkarsh Mangal
The article titled "Insight Is Still the Currency of Data Science" discusses how coding agents free up time for discovery and argues that review practices should evolve to align with analytical work. It emphasizes the importance of focusing on insight rather than merely producing code. The piece was originally published on Towards Data Science.
By Andrew Hinton
How AI has massively changed my day-to-day workflow The post A Day in the Life of a Data Scientist in 2026 appeared first on Towards Data Science .
By Haden Pelletier