His contributions and expertise have led to numerous startups and nonprofits inviting him to serve as an advisor. He gives insight into how what sparked his interest into the data science field, his tips for beginners in data science, and how he stays motivated.

Paul shares with us his powerful journey from being a high school dropout to getting his PhD in computational social science and becoming the A.I. research leader for the Consumer and Industry Lab at Ericsson Research. This episode is packed with advice, wisdom, and tips that will change your mindset.

WHAT YOU WILL LEARN

[21:37] How A.I. can help fight COVID-19
[27:15] Extended reality vs. virtual reality
[32:11] Tips for breaking into data science
[35:29] Important soft skills for data scientist
[44:22] Staying motivated in difficult times

QUOTES
[19:05] "Data science is really a collective endeavour… even the most skilled and successful data scientist is going to have to be able to successfully work with technical stakeholders, non-technical stakeholders…"

[34:51] "…Start from a position of humility…that that can go much further for data scientists than always trying to be the smartest technical person in a conversation…"

[45:29] "Having fun and staying connected and staying entertained is actually part of your job responsibilities rather than something that can be set aside."

SHOW NOTES
[00:01:40] Introduction for our guest today

[00:03:38] What sparked your interest in the field of Data Science? Where did you start and how did you get to where you are today?

[00:05:50] How to not be afraid of math and overcome imposter syndrome

[00:07:42] Where do you see the field of Data science machine learning and A.I. headed in the next two to five years?

[00:09:38] What do you think will be the biggest area of concern for the application of A.I. in the next, say, two to five years?

[00:11:22] What do you think will separate the great Data scientists from the good ones?

[00:12:57] Ericcson's involvement with the White House Office of Science and Technology COVID-19 open research dataset challenge using information retrieval and NLP

[00:13:24] What is information retrieval?

[00:14:02] What is Natural Language Processing?

00:14:40] How information retrieval and Natural Language Processing played a role in the innovative solutions that Ericsson data scientists developed for the challenge.

[00:19:31] What the resulting product looked like

[00:20:52] Interesting findings that came from the challenge

[00:24:30] Congratulations on your new role. AI Research Leader for the consumer and industry lab. So can you tell us a little bit about how the consumer and industry lab fits into Ericsson?

[00:26:56] What XR and VR are and share with us what aspects of XR and VR are most interesting to you.

[00:31:45] How to build a culture of data science

[00:35:13] What do you look for in a data scientists beside those those technical skills?

[00:37:47] How to gain industry experience if you don't have any

[00:39:52] How to communicate with executives as a data scientist

[00:42:10] Thought leadership in data science

[00:44:06] Tips to stay motivated when you're feeling down in your learning journey

[00:47:03] What's the one thing you want people to learn from your story?

[00:48:40] The lightning round

Special Guest: Paul McLachlan, PhD.