Emily Robinson & Jacqueline Nolis - How To Jump Into Data Science from Any Background? #76
Biography
Emily Robinson works at Warby Parker as a senior data scientist on a centralized team tackling some of the company’s biggest projects. Previously, she was at DataCamp, where she built and ran their experimentation analytics system, and at Etsy, where she worked with their search team to design, implement, and analyze experiments. I regularly give talks on A/B testing, R programming, and data science career advice at conferences and meetups (see all talks here) (www.hookedondata.org/about)
Jacqueline Nolis is a data scientist in Seattle with over a decade of experience helping business solve problems with data. Today she works at Brightloom as a principal data scientist where she builds tools to help companies use data to improve customer experience.
Jacqueline has aided companies and led teams at places from DSW and Union Bank to Microsoft and Airbnb. She bas spent years consulting both independently and with consulting firms.
Jacqueline earned a PhD in industrial engineering from Arizona State University. Her academic research covered optimizing road networks for electric vehicles.
Jacqueline coauthored the book Build Your Career in Data Science with the excellent Emily Robinson. This book is a great resource for people wanting to become data scientists or grow in the role. (www.jnolis.com)
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A note from Grant
Today’s episode is a bit of a special one in that we are going to interview not one, but two guests today. They are the co-authors of “Build a Career in Data Science”, a book from Manning Publications, who just so happen to also be the publisher of my book, Taming Text.
Our first guest, Emily Robinson, was a Decision Sciences and Stats major at Rice University who then went on to get a master’s in organizational behavior from INSEAD. She then launched her career working as a professional data scientist for the likes of Etsy, Data Camp and now Warby Parker.
Our second guest, Jacqueline Nolis, has a background in applied mathematics, getting both her bachelor’s and masters from Worcester Polytechnic Institute and her doctorate from Arizona State in industrial engineering. From that foundation she has built out a career as a business analyst, data scientist and director of analytics for the likes of Boeing, Lenati, Vistaprint and now, she’s on her own, as a Principal Data Scientist for her consulting company, Nolis LLC.
Stay tuned as we hear both of their stories as well as learn their tips to building a successful career in data science.
Episode Summary
“In academia I had professors that were still doing revisions for a final version of a paper that they submitted 5 years ago. So it could take a long time to see impact and even when its published it may or may not reach that many people.”
“Jacqueline and I wanted to debunk some myths like you need a specific degree or you need to learn a long list of algorithms or that data science is all about the technical skills.”
“We interview 16 different data scientists in our book. And a key point a lot of them make is yes you need those foundational technical skills but you also need communication skills when working with stakeholders, and skills like writing a resume, and interviewing for a job.”
-–Emily Robinson
“I really wanted to get a PhD in using math to solve business problems. There’s a whole branch of math that does that called operations research.”
“To be a good data scientist you have to be failing all the time. These are all experiments. And so you have to be taking risks.”
-–Jacqueline Nolis
Key Milestones
- What inspired Emily and Jacqueline to get into science?
- According to the book, what are 3 different types of data scientists?
- How does industrial engineering intersect with tech?
- What is it like going from PhD to industry? Common difficulties?
- What is organizational behavior? How is it different than management?
- What is operations research and how does it cross paths with data science?
- The background story of the book Build Your Career in Data Science
- What does failure look like as a data scientist?
- At a meta level, writing a book is not an easy thing. What are some approaches for managing the process?
Additional Resources
Emily learned data science from Metis bootcamp - find out more about Metis here
A/B Testing in the Wild - talk by Emily https://www.youtube.com/watch?v=SF-ryGgLOgQ
Josh Willis, former director of data engineering at slack, on Develomentor - click here for full episode and show notes
Connect with Emily Robinson
LinkedIn
Twitter
Hookedondata.org
Datascicareer.com (promo for book)
Connect with Jacqueline Nolis
LinkedIn
Twitter
Jnollis.com
bestbook.cool (promo for book)
