[PODCAST] The Rise of Data Science & Making Job Retraining Work

 

About this Discussion:

What are we going to do when machines can do our jobs more efficiently, cheaper, and make our jobs redundant?

There is no denying that we are living in a world of automation and the exponential growth and value of data. While some may argue that automation, AI, Machine Learning and many other technology innovations will ring the death knell for many jobs, our guest, Dr. Angel Durr sees a way to keep the workforce relevant and employable through Data Science.

After earning her PhD at the University of North Texas, Dr. Durr quickly saw the gap and potential for a new generation of Data Scientists. The result is the only nonprofit organization in the U.S. that focuses on a life cycle approach to providing data science support: DataReady DFW.  The mission of DataReady is to expand data and data science knowledge among DFW area residents, especially minorities, women, and low-income individuals and eventually spread to cities globally. Her program is making waves and helping those who would normally be left behind, to carve their own path to answer the high demand need for Data Scientists.

About Dr. Angel Durr:

Dr. Durr founded DataReady DFW in summer 2019. She currently serves as the Executive Director of the organization. She earned a PhD in Information Systems in December 2018 at the University of North Texas. Dr. Durr started DataReady DFW after her own experiences as a female minority Data Scientist. She grew up in a single parent household with a parent who was in and out of incarceration. Dr. Durr believes the high cost to entry in Data Science and STEM in general is a barrier for many in undeserved populations. She is dedicated to increasing diversity to move the Data Science profession forward as a discipline. 

You can reach Dr. Angel Durr at LinkedIn: linkedin.com/in/drangeldurr/ 
Website: datareadydfw.org/ 

Here is the Official Breakdown:
4:20     Introductions
5:40     Dr. Durr's Political Science and transition into Data Science
8:05     Data Science's influence on politics and considerations around ethics
9:40     Two sides of ethics: Presention of Data vs. How the Data is Being Used
10:17   Can data be pure? Or is there always bias?
11:24   Statistics without context is meaningless
12:23   Data used in Marketing to prime consumers for a product/solution, not just recognizing customer preference
14:41   Definition of Data Science
17:37   Future of Data will be simplified with easier platforms
18:20   Will Data Scientists become obsolete as AI becomes more sophisticated?
20:47   What is DataReady DFW?
21:00   The two areas of focus: At Risk Communities and K-12 education
24:47   The many different Data Science Disciplines examples: Data Visualization, Data Mining, Data Governance, Data Integrity, Data Analytics
25:45   DataReady DFW Partnerships with Dallas ISD and Girls Scout of North Texas
27:24   Jobs will go away with automation, but DataReady DFW is preparing to train the underprivileged for a skillset that will survive automation
28:11   Dr. Durr's consulting and strategy conversations with businesses, particularly around CRMs
30:37   Biggest challenge is the financials to meet the demand on how to fund the efforts through partnering with both profits and non-profits
33:33   The great potential for corporations to leverage DataReady DFW for projects and in return, giving the students real world experience
35:37   Calling all recruiters to partner with DataReady DFW students as compelling Data Scientists into the city
37:03   Dr. Durr shares that although she is dyslexic and disgraphic, anyone who has an interest and abstract thinking skills can be a Data Scientist
40:13   Why are Data Scientists not IT?
41:33   Should Data Science fall under the Business and not CTO/CIO organization?
42:47   Dr. Durr argues that Data needs to fall under it's own organization because it overlays so many different aspects of business, a Chief "Data or Digital" Officer.
47:30   Diversity and Inclusion in Data Science and business in general


 

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