How AI Is Rewriting the Day-to-Day of Data Scientists

From eliminating low-value tasks to accelerating high-impact projects, here’s how AI is reshaping the data science workflow

In my past articles, I have explored and compared many AI tools, for example, Google’s Data Science Agent, ChatGPT vs. Claude vs. Gemini for Data Science, DeepSeek V3, etc. However, this is only a small subset of all the AI tools available for data science. Just to name a few that I used at work:

• OpenAI API: I use it to categorize and summarize customer feedback and surface product pain points (see my tutorial article).
• ChatGPT and Gemini: They help me draft Slack messages and emails, write analysis reports, and even performance reviews.
• Glean AI: I used Glean AI to find answers across internal documentation and communications quickly.
• Cursor and Copilot: I enjoy just pressing tab-tab to auto-complete code and comments.
• Hex Magic: I use Hex for collaborative data notebooks at work. They also offer a feature called Hex Magic to write code and fix bugs using conversational AI.
• Snowflake Cortex: Cortex AI allows users to call LLM endpoints, build RAG and text-to-SQL services using data in Snowflake.

I am sure you can add a lot more to this list, and new AI tools are being launched every day. It is almost impossible to get a complete list at…