DI Deep Dive Discussion Summary Series

At a recent meeting of the DataInnovators community, the following topics were discussed. Additional discussion summaries are available on Using Analytics in the Sales and Marketing Process and the Vendor Evaluation Process.

Defining Data Science: The Role, Process and Next Steps

How do you define a data scientist?

The ideal data scientist candidate has an academic background, existing institutional knowledge. This person is very analytical with high quality technology skills.

Who qualifies as a true data scientist?

The data scientist works with the data architect to create variables out of existing data. The scientist understands coding with SQL, Python, R and more. It’s important for this person to be connected to the business and industry.

So what’s next?

The issue becomes what to do with this candidate to use their skills to their full potential. It’s not wise to bring in a highly skilled data scientist to have them build models. Data should be in working order first to get the most out of their skill set. From a hierarchy perspective, there is an architect, engineer and modeling. The data scientist is then brought in to add a business lens.

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Interested in having these questions answered?

Join the DataInnovators community and continue the discussion. Contact Kait Bruenn to learn more.