On July 20th, the Cove hosted Tech in Motion for an Orange County tech panel titled, “Data Science – Trusted Relationships and Scientific Innovations.” Tech in Motion is a national event series with the goal of bringing local tech communities together to meet, learn, and innovate. The moderator for the evening was Sean Goodwin, a serial entrepreneur with experience in analytics at several private finance firms (TD Investment Funding & Datacom) and technology in several mobile app startups (DealAppSeo & Fitness Super Pass). The panel discussion explored data science’s application, advancements, and its societal impact.
The conversation began with initial definitions of Data Science for the diverse audience comprised of data scientists, entrepreneurs, investors, and those new to the field. When asked about the difference between Data Analysts and Data Scientists, panelist Xuan Zhao, Data Scientist at Cylance, responded, “What we learn from data can be categorized into the following four levels: data, information, knowledge, and wisdom. Data Analysts work with the first two levels, analyzing the data to pull meaningful information or patterns from it. Data Scientists try to learn from the data and generalize the knowledge obtained to predict trends that go beyond the initial data gathered using machine learning and artificial intelligence.”
On the topic of the origins of data scientists, panelists shared that Data Scientists are born out of a need for research scientists who know more about software engineering. Data Scientists today incorporate domain expertise and business experience with their knowledge of statistics and software engineering. Chris Walker, CTO of Illuminate Education stated, “Data scientists are scientists, but a big part of being a scientist is engaging with people and having the ability to relate to people.” Panelist Amir Zia, Data Scientist at Hart, added, “The profession of data scientists is going to be more fragmented as the discipline continues to grow in its definition. However, the philosophy that data scientists must have a working knowledge of algorithms, statistics, business, and computer science will remain the same.”
Panel topics also included AI’s role in data science and the challenges with gathering data. Regarding AI, panelists shared that as the size and complexity of running algorithms increase, issues arise that existing platforms cannot address right now. As AI continues to develop, these issues may be solved in time. When asked about finding meaning in large data sets, panelist Chris Walker explained, “This is a significant challenge. When capturing all of this data, you need to ensure you are not inadvertently catching bias or other systemic problems.”
The panel concluded by discussing the future of data. Panelist Reza Sadri, Chief Executive Officer of Levy, stated “Data science is going to be something very pervasive and become much more than it is right now. There is a growing need to process larger amounts of data. New algorithms, fast networking, and processing power make it possible for everyone to use data science.” Amir Zia shared, “There is always another thing coming out and it is usually open source. It is amazing how rapidly people are building tools and putting it out there for everyone to use.”