Panel on Important issues facing Women in the Data Science Community (Moderator): Sophia Viklund - Entrepreneur, Board Member and a Public Speaker. Panelists: Dr. Hui Wang, VP of Data Science at PayPal; Dr. Viji Krishnamurthy, Leads Blockchain apps at Oracle; Dr. Sheng You, of FogHorn Systems and Karen Ebert Matthys, Executive Director, External Partners, Institute for Computational & Mathematical Engineering at Stanford.

 

 

Important questions that were discussed:

 

1. How does one choose data science career in college, which factors are influencing the decision to go into data science and which factors encourage or discourage girls to choose this path?

 

2. How can one get started in data science as a change in their career path at mid career point?

3. Will data science as a skill become a must for every engineer to learn in the future or will it be a specialized skillset/role?

4. What engineering or math topics should one study or do a refresh on to prepare herself for a data science career?

5. What constitutes a data science career? In other words, could you please give us some examples of data science related corporate roles or startup jobs?

6. How is data science transforming existing markets - for example: healthcare,
employment/recruitment, retail, governance etc. Is there reason to believe that women in these fields would make different contributions than men, or is the only issue equality of access and opportunity?

 7. Is data science about only algorithms? In other words, do data
 scientists spend most of their time developing and programming algorithms or does this job involve more things that one could do as a data scientist?

 8. Relative to the challenges faced by girls and women who pursue other careers in STEM, what issues, if any, arise uniquely or specifically in data science?

 9. Are they any particular social norms / expectations that limit women/girls from going into computational field/jobs, or data science in particular? How can we help overcome those issues?