The 2020 COVID-19 Computational Challenge has resulted in significant data-driven solutions to assist with the transition to re-open Los Angeles. Team ANRG from University of Southern California with other 5 winner teams produced the COVID-19 infection risk score visuals in different communities within the L. A. County and recommendations on risk mitigation. And data science and tech was an important part of it.
Co-hosted by the City of Los Angeles and Global Association for Research Methods and Data Science (RMDS Lab), the COVID-19 Computational Challenge created innovative solutions to determine the risk of exposure in and around the City of Los Angeles. As Jeanne Holm, Chief Data Officer from the City of L. A., addressed at the opening announcement, “We want to provide this information to the public, so we will not only analyze the data but interpreting it. The result should be actionable and communicable.”
The Challenge attracted 405 contestants of 66 data science teams from universities and research organization all over the world, including Columbia University, Harvard University, University of Michigan, Zhejiang University, Institut National D’Etudes Demographiques, and many more. Throughout the two-week process, competitors received training and mentorship from RMDS Lab, UCLA Computational Medicine, SafeGraph, Snowflake, Esri, Gartner, and LA County Department of Public Health on open data sources, public health policies, data ethics, as well as the case studies for business.
The results were reviewed by a panel of judges from the RMDS Lab, the City of LA, LA County Department of Public Health, Chamber of Commerce, and academia. The winning teams won cash prizes of over $8,000 provided by sponsors who internship opportunities at the City of Los Angeles and UCLA Computational Medicine and the invitation to present at IM Data 2020.
“We are pleased to have this great opportunity to contribute back to our Los Angeles communities and to be a part of a potential powerful solution of assisting the reopening of Los Angeles, as our mission is to utilize data and AI to produce positive social impacts,” says Dr. Alex Liu, the founder of RMDS Lab.
According to the Berkely University, in the past decade, data scientists have become necessary assets and are present in almost all organizations. These professionals are well-rounded, data-driven individuals with high-level technical skills who are capable of building complex quantitative algorithms to organize and synthesize large amounts of information used to answer questions and drive strategy in their organization. This is coupled with the experience in communication and leadership needed to deliver tangible results to various stakeholders across an organization or business.
Data scientists need to be curious and result-oriented, with exceptional industry-specific knowledge and communication skills that allow them to explain highly technical results to their non-technical counterparts. They possess a strong quantitative background in statistics and linear algebra as well as programming knowledge with focuses in data warehousing, mining, and modeling to build and analyze algorithms.
Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.