The Chief Data Scientist sits at a unique crossroads between the data science team and the rest of the C-suite and senior management. As a result, the Chief Data Scientist needs to be able to bridge the gap between business objectives (from initial strategy planning to reporting on KPIs) and data projects. In this article, we highlight some of the additional skill sets necessary to become a Chief Data Scientist, as well as primary responsibilities of those inhabiting the role.
To begin, it’s important to preface this kind of discussion around job titles with the fact that each organization is different and will have a different structure based on elements such as company size, data team size and composition, industry, and so on. Skills Chief Data Scientists should have include:
- Expert knowledge in statistics, programming languages, database technology, and data visualization
- The ability to engage with both technical and non-technical audiences and explain the business value of a given project
- Strong communication skills, business acumen, and knowledge of the industry s(he) works in
- While not a required qualification, many Chief Data Scientists have a computer science, engineering, or related degree
- A significant number of years of “in the field” practitioner experience under his or her belt, likely determined by the company hiring
Key Chief Data Scientist Responsibilities
1. Helping data teams determine the best route for tackling use cases (which might be determined by understanding the scope, identifying possible techniques and approaches, and outlining both the business and technical advantages or drawbacks to each one)
2. Navigating ethical concerns around machine learning and ways to address them (including but not limited to establishing a sound governance strategy, standards for data quality and integrity, and a Responsible AI framework)
3. Maintaining a pulse on the various data science, machine learning, and AI projects throughout the organization in order to effectively track progress and results
4. Communicating updates back to the business, such as KPIs from the data science team, as well as communicate the team’s short- and long-term goals and vision to help them gain buy-in from other business units
It is important to note, though, that the Chief Data Scientist role is not one-size-fits-all and his or her responsibilities will likely vary depending on the size of the organization. In a small or medium-sized business, for example, the Chief Data Scientist might be performing more technical work (i.e., prototyping and implementing models, vetting data quality, and so on), whereas in larger companies, this person might be doing less technical work such as building out a data governance strategy, enabling democratization by identifying processes for scaling, and so on.