In this interview with Data Scientist Mark Meloon, we turn the tables and I provide advice to “aspiring” Data Scientists on how to land that first job. It’s broker down into 10 Parts (by question.). Enjoy!
When author Kate Strachnyi wanted to learn more about data science, she went straight to the source. In a series of more than twenty interviews, she asks leading data scientists questions about starting in the field and the future of the industry. Strachnyi’s interview subjects include team members from some of the world’s largest organizations, including LinkedIn, Pinterest, Bloomberg, and IBM.
Some Thoughts on Mid-Career Switching Into Data Science Posted by William Vorhies on October 3, 2017 at 7:06am View Blog Summary: If you are mid-career and thinking about switching into data science here are some things to think about in planning your journey. We get lots of inquiries from readers asking for career advice and many […]
“Scaling makes your life difficult, Scaling can take hours, days, or weeks to perform which may delay needed data processing”
(Refreshed Post) Predictive Analytics Made Easy!
Download this free eBook now and see how you can start using Predictive Analytics today to drive business decisions! Read More
This book has been written in layman’s terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, they stick to intuitive explanations and visuals.
Watch Video to learn about how Zillow’s Data Science team builds it Recommender Systems and read how DevOps does “Continuous Delivery and Deployment for Zestimates”.
(Reposted due to popular demand) Another great video from Josh Wills. Josh is Sr. Director of Data Science at Cloudera and has a gift for making fairly complicated technology explanations very digestible to the novice and intermediary techie.
What I most love about this video is how Josh explains -very clearly – the issue of translating analytics Machine Learning on a large set of data records (many individuals) and making it work well in a “real life” production environment on a single individual (think eCommerce). Watch Video
In 2013, Airbnb had a small, centralized team of five data scientists serving the data needs of the company. Since then, they have grown to become one of the largest, most innovative startup teams with over 70 data scientists now serving separate business units. In addition to setting a consistently high bar on new hires and focusing on technical mentorship from peers, the structure of the organization has been key to successful growth. Read More
VIDEO PODCAST | In Episode 5 of this podcast series by Renee Teate of “Becoming a Data Scientist”, she interviews Clare Corthell, founding partner of summer.ai and creator of the Open Source Data Science Masters curriculum, about becoming a data scientist. Read More