Towards Data Science has announced a major overhaul of its website and contributor portal. The new site promises faster performance and a brand‑new portal for writers, aiming to improve the experience for both readers and contributors. The update is positioned as a significant upgrade for anyone who reads, writes, or both on the platform.
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.
A reflection on the first month of learning data engineering in public, and what actually kept me going. The post One Month Into Learning Data Engineering in Public: Here’s What I Didn’t Write About appeared first on Towards Data Science .
The true bottleneck was never the analysis. The post BI Is Dead, Long Live BI appeared first on Towards Data Science .
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 .
The article titled "How to Format Your TDS Draft: A New and Improved Guide" provides comprehensive instructions for creating a draft on the Towards Data Science Contributor Portal. It outlines the necessary steps and formatting guidelines to ensure a polished submission. The guide aims to streamline the drafting process for contributors.
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.
$8 million vs $5k + Potentially Going Viral The post When Data Science Makes Us Sad: The Story of an Overbooked Flight appeared first on Towards Data Science .
The downside of conference travel The post Last Month’s Machine Learning Lessons Learned appeared first on Towards Data Science .
The article examines the emerging data science roles that have surfaced following the Large Language Model boom, focusing on AI Engineers, Applied Scientists, and Forward Deployed Engineers. It explores how these positions differ and what responsibilities they entail in the current AI landscape. The piece provides an overview of each role’s unique contributions to the development and deployment of AI technologies.
The article titled "Deploying Data Science Tools: Part 1" discusses how to get your data science code running anywhere. It focuses on the practical steps and considerations for deploying data science tools across different environments. The post was originally published on Towards Data Science.
The article discusses how context engineering is evolving and outlines practical ways data scientists can incorporate the newest guidelines into their everyday work. It explains the importance of adapting to these changes to improve model performance and relevance. The piece offers actionable steps for integrating context engineering into typical data science workflows.
I tried to make my ETL pipeline production-ready. Three things broke.