By AI Trends Staff
The role of the Chief Data Scientist is needed to help the Chief Technology Officer bridge to business managers who are defining how AI is to deliver on the company’s business strategy.
The required amount of guidance and monitoring of data scientists is not likely to happen from the CTO’s office, suggest experts.
“You need a Chief Data Scientist to bridge the gap between management and the data scientists, to help explain what machine learning can do and cannot do,” stated Ira Cohen, cofounder and chief data officer of Anodot, a data analytics company that uses AI and machine learning, in an account from Analytics Insight. “You need somebody who understands what it is in a deeper form than a CTO, who might have a broader knowledge of a lot of things, but not necessarily machine learning.”
Business departments can have data silos that could present obstacles or challenges to getting the data required to make needed machine models work.
Specialist roles that span different parts of the analytics process as well as different specialties within data science have emerged. However, many of the people in these roles are either relatively junior or are experienced but primarily interested in the technical execution of projects, as opposed to worrying about staffing issues, budget planning, and corporate politics, suggests a recent account from the International Institute for Analytics.
Executives set the priorities and make the call as to what analytics are most needed, and the hands-on technical analysts handle gathering data, coding, and delivering the analytics. “In between these organization chart extremes, organizations need to consider adding one more role to their team.”
“The early generations of analytics and data science executives were people who had technical backgrounds with substantial coding and model building experience,” stated Bill Franks, chief analytics officer with IIA, author of the account. “In today’s world, management skills and a strategic viewpoint are at least as important as technical skill, if not more important, for an analytics executive. This is due to the size, scale, and broad reach of today’s analytics and data science organizations within large companies.”
The names for this new leader that combines technical experience and a strategic business viewpoint is the Chief Data Scientist, the author suggests.
The profile of the Chief Data Scientist is someone with experience and success in building and deploying models. Senior in tenure, the Chief Data Scientist prefers to remain hands-on and involved with execution, as opposed to moving up in the management ranks. “As one of the most skilled technic
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