Leveraging Data Scientists and Business Expectations During the COVID-19 Pandemic
This addresses operational challenges for data science teams in IT during crises, but it is incremental as it discusses lessons learned without introducing new methods.
The article examines how a data science team, organized as a skunk works group, managed productivity and practices during the COVID-19 pandemic, focusing on maintaining stakeholder expectations and project quality in an IT context.
The COVID-19 pandemic presented itself as a challenge for separate societal sectors. On the information technology (IT) standpoint, it does include the maintenance of the infrastructure required to hold collaborative activities that went to happen online; the implementation of projects in a scenario of uncertainty; and keep the software engineering and information security best practices in place. This article presents the context of a data science team organized as a skunk works group composed of professionals with experience in both the industry and academia, located in an IT department working with a team of seasoned data engineers. At the time the pandemic started, the relatively new data science team was positioning itself as a Center of Excellence in Advanced Analytics. With the pandemic, it had to keep up with the expectations from the stakeholders; manage current and upcoming data science projects within the methodology practiced in IT; and maintain a high level in the quality of service delivered. This article discusses how did the COVID-19 pandemic affected the team productivity and its practices as well as the lessons learned with it.