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Professions don’t change overnight, and you can rarely point to a single moment that transforms them forever. Complex processes like these happen over time, and require the accumulation of countless new habits, tools, and business decisions.
This week, we highlight three excellent articles on the current state of data science. They tackle the topic from different angles, but they all share a keen awareness of the ever-expanding adoption of AI-powered workflows, and how the latter have made data science a strikingly different discipline in the span of a couple of years (give or take). Let’s dive in.
How I Used ChatGPT to Land My Next Data Science Role
Beyond algorithms and Python, the job search might be the biggest common denominator for data practitioners these days. It’s a (sometimes scary) new world where shifting role definitions and the growing presence of LLMs at every step of the hiring pipeline have made a stressful process even tougher to navigate. Yu Dong‘s new article suggests it’s time to flip the script, and shows how to leverage tools like ChatGPT to boost your chances as an applicant.
Past is Prologue: How Conversational Analytics Is Changing Data Work
Whitney Marks shares clear and actionable insights on how to thrive amid the transition she sees across data teams: no longer mere dashboard and model builders, their future success relies on easing into the role of AI managers.
How the Rise of Tabular Foundation Models Is Reshaping Data Science
Structured data remains a challenge even for the most advanced LLMs. As Pirmin Lemberger explains, new foundational models are changing that, and could make databases and spreadsheets more easily digestible for generative AI.
This Week’s Most-Read Stories
From an agentic AI tutorial to a primer on data visualization, don’t miss the articles that resonated the most with our readers in the past week.
How to Perform Effective Agentic Context Engineering, by Eivind Kjosbakken
Data Visualization Explained (Part 3): The Role of Color, by Murtaza Ali
Plotly Dash — A Structured Framework for a Multi-Page Dashboard, by Michael Clayton
Other Recommended Reads
If you’re in the mood for exploring more topics, approaches, and tools this week, we’ve got you covered with these top-notch contributions.
- MobileNetV2 Paper Walkthrough: The Smarter Tiny Giant, by Muhammad Ardi
- 10 Data + AI Observations for Fall 2025, by Barr Moses
- How to Spin Up a Project Structure with Cookiecutter, by Elena Jolkver
- Dreaming in Blocks — MineWorld, the Minecraft World Model, by Youssef Farag
- Classical Computer Vision and Perspective Transformation for Sudoku Extraction, by Florian Trautweiler
Meet Our New Authors
We hope you take the time to explore the excellent work from the latest cohort of TDS contributors:
- Illia Smoliienko unpacks the limitations of AI in analytics through the example of bearing-vibration data analysis.
- Elisha Rosensweig and Eitan Wagner pour some cold water on the notion that vibe-coding is somehow an improvement over traditional programming.
We love publishing articles from new authors, so if you’ve recently written an interesting project walkthrough, tutorial, or theoretical reflection on any of our core topics, why not share it with us?
