Build A Career in Data Science | Jacqueline Nolis and Emily Robinson

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

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