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Adam Ross Nelson on Getting Started in a Data Science Career
Podcast |
Data Driven
Publisher |
Data Driven
Media Type |
audio
Categories Via RSS |
Life Sciences
Mathematics
Science
Technology
Publication Date |
Aug 30, 2023
Episode Duration |
01:29:51

On this episode of Data Driven, Frank and Andy interview Adam Ross Nelson. Adam is a consultant, where he provides insights on data science, machine learning and data governance. He recently wrote a book to help people get started in data science careers. 

Get the book

How to Become a Data Scientist: A Guide for Established Professionals

Speaker Bio

Adam Ross Nelson is an individual who initially pursued a career in law but ended up making a transition into education. After attending law school and working in administrative and policy roles in colleges and universities for several years, Adam hit a plateau in his career. Despite being a runner-up in national job searches multiple times, he felt that his lack of a PhD hindered his advancement in academia, while his legal background prevented him from being taken seriously by law professionals. Consequently, Adam decided to pursue a PhD in order to overcome this hurdle. During his PhD program, Adam discovered his passion and knack for statistics. His focus shifted towards predictive analytics projects, specifically ones related to identifying students in need of academic support. As he shared his work with friends, family, and coworkers, they began referring to him as a data scientist, a label that Adam initially resisted due to his legal and educational background. However, he eventually embraced the moniker, and even his boss started referring to him as the office's data scientist, despite HR not recognizing the title.

Show Notes

[00:03:26] Transitioning from law to education administration, plateaued career, runner-up in job searches, pursued PhD, became data scientist.

[00:08:58] Data seen as liability, now asset. Examples: DBA's OLAP analysis, Walmart's weather-based inventory management.

[00:12:56] Dotcom crash aftermath: fierce competition for jobs.

[00:22:48] Salespeople have deep-seated insecurities and unique perspective.

[00:29:31] Various classifications of data scientists and career advice.

[00:35:55] "No full-field midfielder, data science is teamwork"

[00:39:23] Navigating job descriptions for transitioning professionals.

[00:42:56] Career coach helps professionals transition into data science.

[00:49:41] First job: English teacher in Budapest, Hungary. Second job: Speaker for Mothers Against Drunk Driving.

[00:56:30] Concerns about reliance on technology, especially AI.

[01:00:22] Food options in lobbying are better in DC & state capitals. Also, check out the funny WY Files YouTube channel.

[01:04:21] You can't separate them: LLM, bias, internet.

[01:10:23] Ethics in consulting and avoiding dilemmas.

Join hosts Andy Leonard, BAILeY, and Frank La Vigne as they dive into the world of data science in the podcast 'Data Driven.' In this episode, they interview guest Adam Ross Nelson on the topic of getting started in a data science career. Discover how data science can contribute to a company's revenue and bottom line, even in non-profit organizations. Learn about real-life use cases of data science, such as predicting the best ask in fundraising, and the importance of specific suggestions during interviews. Get valuable insights on transitioning into a data science career and the evolving perception of data. Don't miss out on engaging discussions, expert advice, and practical tips. Tune in to 'Data Driven' for all things data science!

On this episode of Data Driven, Frank and Andy interview Adam Ross Nelson. Adam is a consultant, where he provides insights on data science, machine learning and data governance. He recently wrote a book to help people get started in data science careers. 

Get the book

How to Become a Data Scientist: A Guide for Established Professionals

Speaker Bio

Adam Ross Nelson is an individual who initially pursued a career in law but ended up making a transition into education. After attending law school and working in administrative and policy roles in colleges and universities for several years, Adam hit a plateau in his career. Despite being a runner-up in national job searches multiple times, he felt that his lack of a PhD hindered his advancement in academia, while his legal background prevented him from being taken seriously by law professionals. Consequently, Adam decided to pursue a PhD in order to overcome this hurdle. During his PhD program, Adam discovered his passion and knack for statistics. His focus shifted towards predictive analytics projects, specifically ones related to identifying students in need of academic support. As he shared his work with friends, family, and coworkers, they began referring to him as a data scientist, a label that Adam initially resisted due to his legal and educational background. However, he eventually embraced the moniker, and even his boss started referring to him as the office's data scientist, despite HR not recognizing the title.

Show Notes

[00:03:26] Transitioning from law to education administration, plateaued career, runner-up in job searches, pursued PhD, became data scientist.

[00:08:58] Data seen as liability, now asset. Examples: DBA's OLAP analysis, Walmart's weather-based inventory management.

[00:12:56] Dotcom crash aftermath: fierce competition for jobs.

[00:22:48] Salespeople have deep-seated insecurities and unique perspective.

[00:29:31] Various classifications of data scientists and career advice.

[00:35:55] "No full-field midfielder, data science is teamwork"

[00:39:23] Navigating job descriptions for transitioning professionals.

[00:42:56] Career coach helps professionals transition into data science.

[00:49:41] First job: English teacher in Budapest, Hungary. Second job: Speaker for Mothers Against Drunk Driving.

[00:56:30] Concerns about reliance on technology, especially AI.

[01:00:22] Food options in lobbying are better in DC & state capitals. Also, check out the funny WY Files YouTube channel.

[01:04:21] You can't separate them: LLM, bias, internet.

[01:10:23] Ethics in consulting and avoiding dilemmas.

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