Pick The Right Voices To Listen To | Brenda Hali

On this episode of The Artists of Data Science, we get a chance to hear from Brenda Hali, a marketing guru turned data scientist who is passionate about using data to understand causation and to promote company growth. She gives insight into how she broke into the data science field, how marketing and data science are related in some ways, and the struggles she faced when breaking into tech.

Brenda shares with us her transition from marketing into data science, along with the importance of having the representation of women and other minorities in the tech industry. This episode really shows why diversity and inclusion in tech is so important, and how we can all play a role to help others break into the field.

WHAT YOU'LL LEARN

[6:56] What marketers can learn from data scientists

[11:07] Steps to take when beginning a new project

[17:33] How to communicate effectively with your team in the post-COVID world

[20:56] Advice for women and minorities that want to enter into data science

QUOTES

[15:02] “...you need to have communication with your team, and that communication needs to be in one place”

[15:47] “...experiment fast and let things go…”

[23:52] “Be careful with who you listen to, and be careful when those voices are close to you.”

FIND BRENDA ONLINE

LinkedIn: https://www.linkedin.com/in/brenda-hali

Instagram: https://www.instagram.com/datanauti/

Twitter: https://twitter.com/brendahali

Medium: https://medium.com/@brendahalih

SHOW NOTES

[00:01:31] Introduction for our guest today

[00:02:19] Let's talk a little bit about how you first heard of data science and what drew you to the field.

[00:06:16] As someone who is a marketer turned data scientist, what would you say that the data scientist and the marketer can learn from each other?

[00:08:46] How do you see data science impacting marketing and what could the data scientists and the marketer do to best serve each other in this vision of the future that you have?

[00:10:49] What are some of the first things that you do when taking on a new project? And what are some of the steps you take to kind of keep you on track while going through and navigating the ambiguity of a data science project?

[00:12:51] You wrote on a "Starting Guide to Excel at Teamwork." I was wondering if you could talk to us a bit about the importance of teamwork for data scientists. Do you mind sharing the key points from that post with our audience?

[00:17:17] How do you think teamwork will change or be affected in this post-Covid world? What can we do to start being better team members when we're actually not going to be for a while at least some people aren't going to be in the same room, in the same office as their colleagues.

[00:20:38] Do you have any advice or words of encouragement for the women in our audience who are breaking into tech or who are currently in the tech space.

[00:24:11] What can the Data community do to foster the inclusion of women in Data science and A.I?

[00:29:37] What's the one thing you want people to learn from your story?

[00:31:39] How universities, probably will change their business model.

[00:32:27] What is your Data science superpower?

[00:33:03] What's an academic topic outside of Data science that you think Data scientists should spend some time researching on?

[00:33:13] What is the number one book, fiction, non-fiction or both that you would recommend our audience read. And what was your most impactful takeaway from it?

[00:34:09] What's the biggest blunder of bias you've seen or heard of with an algorithm?

[00:34:55] If we can somehow get a magic telephone that allowed you to contact 20 year old Brenda, what would you tell her?

[00:35:43] What's the best advice you have ever received?

[00:36:23] What motivates you?

[00:38:08] What song do you have on repeat?

[00:38:21] How can people connect with you? Where can they find you?