Build A Career in Data Science | Jacqueline Nolis and Emily Robinson
October 5th, 2020
1 hr 15 mins 6 secs
Season 6
About this Episode
Jacqueline Nolis is currently a principal data scientist at Brightloom where she creates models to help restaurants and retailers improve the customer experience.
Emily Robinson is currently a senior data scientist at Warby Parker, where she works on a centralized team tackling some of the company’s biggest projects.
WHAT YOU'LL LEARN
[00:10:42] The three types of data scientists
[00:13:09] How to make an effective analysis
[00:16:08] How to convert a business problem into a data science problem
[00:19:39] What the heck is deploying a model into production mean anyways?
[00:29:57] Who are the various types of stakeholders that we may encounter in our data science career and what do they care about?
[00:37:56] How to build a data science practice as the first data scientist
FIND JACQUELINE ONLINE
Website: https://jnolis.com/
LinkedIn: https://www.linkedin.com/in/jnolis/
Twitter: https://twitter.com/skyetetra
GitHub: https://github.com/jnolis
FIND EMILY ONLINE
Website: https://hookedondata.org/
LinkedIn: https://www.linkedin.com/in/robinsones/
GitHub: https://github.com/robinsones
SHOW NOTES
[00:01:46] Guest introduction
[00:03:15] The path into data science
[00:04:58] How they met
[00:05:37] Challenges of working on a book online and across time zones
[00:07:50] Silly frustrations while writing the book
[00:10:42] The three types of data scientists
[00:13:09] How to make an effective analysis
[00:14:29] Good versus bad analysis
[00:15:21] How are the types of analysis different for the different types of data scientists?
[00:16:08] How to convert a business problem into a data science problem
[00:18:15] What to think about before diving into data and coding
[00:19:39] What the heck is deploying a model into production mean anyways?
[00:22:05] An illustrative example of putting a model into production
[00:23:50] How to keep a model running in production
[00:25:17] At what point do we retrain the model?
[00:28:36] How to handle interview questions about deploying a model to production
[00:29:57] Who are the various types of stakeholders that we may encounter in our data science career and what do they care about?
[00:31:49] Tailor your communication to your audience
[00:33:10] How to decide which projects to take on at work
[00:35:41] How to establish a data culture when you’re the first data scientist in an organization
[00:37:56] How to build a data science practice as the first data scientist
[00:41:11] Non-technical skills for success
[00:43:34] Is data science an art or science?
[00:46:43] The creative process in data science
[00:48:26] Advice for women in data science
[00:51:51] How to promote diversity and inclusion in data science
[00:54:50] What's the one thing you want people to learn from your story?
[00:57:47] The lightning round