Uploaded October 2022 | Updated September 2026, 2 weeks ago
Mark Freeman is a community health advocate turned data scientist His mission is to improve the well-being of people, especially among those marginalized. He is currently a senior data scientist at Humu where he builds data tools that drive behavior change to make work better. He has a master degree from the Stanford School of Medicine in clinical research, experimental design and statistics. He also has a certificate in entrepreneurship from the Business School of Stanford. In his free time, he volunteers with a Bay Area Community Health Advisory Council. He also plays Men's Division III Rugby. We talked about the building data tools, data engineering skills for data scientist, how to pitch a projects, and his career journey. If you like the show, subscribe to the channel and give us a 5 star review. Subscribe to Daliana's newsletter at dalianaliu.com for more on data science and this podcast.
Mark's LinkedIn: linkedin.com/in/mafreeman2
Daliana's LinkedIn: linkedin.com/in/dalianaliu
Daliana's Twitter: twitter.com/DalianaLiu
0:00 Intro
00:03:05 Our experience using R - 1000 lines of code
00:09:22 Entrepreneurship within a company
00:16:25 DBT and modern data stack
00:20:15 Tools don’t matter (in interviews)
00:21:09 Things DE enjoys but DS doesn’t
00:24:55 How to work with different stakeholders
00:30:32 Common SQL mistakes
00:33:34 SQL vs Python vs R
00:35:26 T.R.I.B.E framework for projects
00:40:43 Meet the stakeholders where they at
00:42:40 Use feedback to get buy-in from collaborator
00:46:36 How to pitch a new idea
00:49:45 Don’t lead with solution, lead with the problem
00:51:03 How to get buy-in from the leadership
00:57:56 Present an idea as if the audience came up with it
00:58:41 How to iterate a project
01:00:27 How he almost lost 1 Million dollar for his company
01:02:07 Things he learned from his manager
01:04:19 Things that help people make changes effectively
01:06:05 Things he learned from mentoring
01:12:19 Mental Health and anxiety
01:17:12 Web3
01:20:14 Why he cares about community health
01:25:40 "Soul - searching" on his future
01:28:36 Why he write on LinkedIn
01:30:04 Future of data science
Mark Freeman is a community health advocate turned data scientist His mission is to improve the well-being of people, especially among those marginalized. He is currently a senior data scientist at Humu where he builds data tools that drive behavior change to make work better. He has a master degree from the Stanford School of Medicine in clinical research, experimental design and statistics. He also has a certificate in entrepreneurship from the Business School of Stanford. In his free time, he volunteers with a Bay Area Community Health Advisory Council. He also plays Men's Division III Rugby. We talked about the building data tools, data engineering skills for data scientist, how to pitch a projects, and his career journey. If you like the show, subscribe to the channel and give us a 5 star review. Subscribe to Daliana's newsletter at dalianaliu.com for more on data science and this podcast.
Mark's LinkedIn: linkedin.com/in/mafreeman2
Daliana's LinkedIn: linkedin.com/in/dalianaliu
Daliana's Twitter: twitter.com/DalianaLiu
0:00 Intro
00:03:05 Our experience using R - 1000 lines of code
00:09:22 Entrepreneurship within a company
00:16:25 DBT and modern data stack
00:20:15 Tools don’t matter (in interviews)
00:21:09 Things DE enjoys but DS doesn’t
00:24:55 How to work with different stakeholders
00:30:32 Common SQL mistakes
00:33:34 SQL vs Python vs R
00:35:26 T.R.I.B.E framework for projects
00:40:43 Meet the stakeholders where they at
00:42:40 Use feedback to get buy-in from collaborator
00:46:36 How to pitch a new idea
00:49:45 Don’t lead with solution, lead with the problem
00:51:03 How to get buy-in from the leadership
00:57:56 Present an idea as if the audience came up with it
00:58:41 How to iterate a project
01:00:27 How he almost lost 1 Million dollar for his company
01:02:07 Things he learned from his manager
01:04:19 Things that help people make changes effectively
01:06:05 Things he learned from mentoring
01:12:19 Mental Health and anxiety
01:17:12 Web3
01:20:14 Why he cares about community health
01:25:40 "Soul - searching" on his future
01:28:36 Why he write on LinkedIn
01:30:04 Future of data science
