Does the role of a Data Scientist shift toward data quality management?

All answers to this question.

You are definitely not alone in this. A study I read recently mentioned that data scientists spend up to 80% of their time on data preparation. At my previous firm, we realized that data quality was too important to be siloed, so we integrated it into the entire lifecycle. While it feels like "librarian work," the reality is that a model is only a mathematical representation of your data. If you don't understand the nuances of the data's quality, you can't build a robust model. It’s a trend that’s here to stay until automated tools become much more sophisticated.

   Answered 2025-02-05 by Cynthia Moore

Cynthia, do you believe that specialized "Data Quality Engineer" roles will eventually take this burden off the data scientists?

   Answered 2025-02-07 by Robert Nelson

• Robert, I actually see that happening already. Many large enterprises are hiring for specific data reliability and quality roles to ensure the scientists can focus on high-level architecture.

     Commented 2025-02-08 by Matthew King

In my experience, even with engineers, the scientist must oversee the data quality to ensure the specific features needed for the model are actually representative.

   Answered 2025-02-09 by Lisa Anderson

• Spot on, Lisa. You can't fully outsource the understanding of the data. The scientist needs to be "hands-on" with the raw data to spot subtle biases.

     Commented 2025-02-10 by Jason Bennett