Data Scientists May Not Exist, but Data Science Teams Should

Four Best Practices for Accelerating Time-to-Value of Master Data Management

Last month, I pointed out that you’ll probably never hire a data scientist, based on IT consultant Robin Bloor’s view that no such person exists in the real world, because too many skill sets are at play.

Bloor wrote that instead, you’ll develop a team that brings together all the skills of the so-called “data scientist,” such as understanding data, data flows, statistics and your specific business industry.

Evan Levy, partner and co-founder of Baseline Consulting, recently added his voice to the growing list of people who say the data scientist is like a unicorn. Like Bloor, Levy contends a more realistic approach to the scientific study of data is to build a team of people who specialize in each of the areas needed.

Levy goes a step further, though, and explains the six skill sets you should include on a Data Science team:

• A data services expert who can manage the data repositories that will feed data into your analytics effort. Someone skilled in data services will understand data schemas, tracking data content and ensuring the platforms are maintained. One job title example that points to where these skills reside now is database administrators.
• A data engineer to be the person who oversees the technical tooling for moving, processing, integrating and managing the data. “In most analytics environments, these activities are handled by the data integration team,” he writes. But it’s not just extract-transfer-load (ETL) processes anymore. Big Data changes that to include processing data streams and handling the cleansing and standardization of structured and unstructured data sources.
• Data manager—Think of this person as sort of like a source data steward who focuses on supporting development access and manipulating data content.
• Production development includes the person responsible for prepping the data for production. It might include simplifying the end-user tool, setting up new algorithms, using new data attributes, etc. Basically, this person makes sure the discoveries your team makes deliver value to the business, he writes.
• The data scientist—Wait? I thought that was a unicorn? In Levy’s view, whoever is best at analyzing data so that the business can obtain a competitive edge is the data scientist and team lead. 

“They are adept at technical activities and equally qualified to lead a business discussion as to the benefits of a new business strategy or approach,” he writes. “They can tackle all aspects of a problem and often lead the interdisciplinary team to construct an analytics solution.”

He doesn’t specifically mention adding someone who is knowledgeable about the business and your particular industry, but Bloor points out that it’s a good idea to include such a person on your team.