Data Science Influencers: Who’s Leading in Data and Analytics?

Data science influencers are using analytics and algorithms to build and innovate. Learn about these individuals below.

By: Michael Brito

Category: Influencer Marketing

Scroll down for the list of data science influencers.

What is data science?

Data science is the process of extracting knowledge and insights from data. It involves using various techniques, including statistics, machine learning, and data visualization, to analyze data sets and uncover patterns. Data scientists also use their findings to suggest ways to improve business operations or customer experiences.

Why is data science important for business?

Data science can help businesses better understand their customers, improve their operations, and make better decisions. By analyzing data, companies can identify trends and patterns that they can use to their advantage. For example, a retail business might use data science to analyze customer purchase history to recommend what products to stock or price items.

My methodology for identifying and measuring influence differs slightly from others in the industry. For the most part, power is measured using three core social data points-reach, relevance, and resonance:

  • Reach: Community size. Essentially it is an aggregate sum of an influencer’s audience across all channels.
  • Topical Relevance: Volume. In other words, how often is the influencer talking about and mentioning the core topics across their social channels? Was it a mention in a YouTube video three years ago, or do they consistently talk about it in the media where they participate the most?
  • Resonance: Engagement. When they mention the topics in question, are audiences engaging with the content? Is it resonating with them?

I want to add a layer of influencer analytics, but it’s somewhat of a manual process. I like to call it a reference, and it answers the following questions:

  • Is the influencer referenced by other influencers?
  • Is the influencer referenced by traditional media?
  • Is the influencer mentioned by a specific audience important to the brand?

Unfortunately, some of this analysis must be done manually, but this is good. It requires spending some time in the data and providing contextual insights as to why you chose this influencer.

Data Science Influencers

For your convenience, I created a Twitter list of the 10 data science influencers.

DataScience Influencers

Here are a few other influencer lists in case you are interested:

I put together some helpful tips on how to work with technology influencers. You can use this as a blueprint when you are identifying the most relevant influencers and launching your program.

Influencer Marketing Guide


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