Weapons of Math Instruction: Shifting from Data-Driven to Science-Driven Product Development
This talk was held on Wednesday, May 30, 2018.
Data is a hammer, science is carpentry.
Building great technology products is difficult — scaling them presents even more challenges. The sheer amount of data now available can help with decision making for your products, and many companies are striving to be more data-driven. Data is only the start of the solution. Without a scientific process for consuming this data and deriving its meaning, you can end up with lower quality decisions and potentially slower decision velocity due to analysis paralysis. Teams can become distracted by the noise of large quantities of data and miss vital information. Thankfully, you can rely on scientific principles to refine and scope your use of data so that you’re asking the right questions at the right time in search of meaningful answers that will help you improve your products.
In this talk, I will introduce you to key data science concepts and illustrate how to use them in making robust decisions at scale. This talk leverages established principles from statistics, information theory, economics, and machine learning, to supply your team with a shared vernacular and evaluation framework. There will be math, but also practical examples and even some March madness in May!
Donal McMahon is a director of data science at Indeed.
Originally published at Indeed Engineering Blog.