When our Sr. Data Scientists aren't teaching the intensive, 12-week bootcamps or corporate training courses, they're working on a variety of other projects. This monthly blog series tracks and discusses some of their recent activities and accomplishments.
Data scientists are in high demand, particularly as data changes the way many companies do business. But it can be difficult to attract (and retain) data science talent in a job market that is growing at an unprecedented rate. In this post, Metis Sr. Data Scientist Brendan Herger draws on years of experience to share how to effectively and efficiently hire data scientists and build out your team.
Too often we assume that good data science translates to effective data science, even though it's untrue. This assumption has killed many would-be successful projects. In this post, Sr. Data Scientist Kerstin Frailey introduces the impact hypothesis, or, how to critically scope and communicate how a project will drive impact. Doing this will transform the way data science drives your business.
After 20+ years of working as a senior-level software engineer for companies like Goldman Sachs and Bank of America, Emy Parparita was looking for a change. Read how the bootcamp helped him transition to his current role of Machine Learning Engineer at Quora.
We hosted an AMA (Ask Me Anything) session on our Community Slack channel with Nathan Grossman, Data Scientist at Wells Fargo and instructor of our next Beginner Python and Math for Data Science course. Check out some highlights from the Q&A here.
We love nothing more than spreading the news of our Data Science Bootcamp graduates' successes in the field. Here, enjoy a video interview produced by Heretik, where graduate Jannie Chang now works as a Data Scientist, then read an interview between deeplearning.ai and graduate Joe Gambino, Data Scientist at IDEO.
In an excellent new interview conducted by Burtch Works, our Director of Data Science Corporate Training, Michael Galvin, discusses the value of "upskilling" your team, how to improve data literacy skills across your company, and why Python is the programming language of choice for so many.
This blog series tracks and discusses the recent activities and accomplishments of our talented Sr. Data Scientists. This month, read advice from the team on how to manage your own data team's curiosity, how to democratize data for all, how to create function factories in Python, and more.
Democratizing data means more than just enabling your employees to make queries on the data. It means helping them develop the skills to read graphs, think about relevant scales, and interpret what the data is saying. In this post, Sr. Data Scientist Damien Martin shares how training your team leads to better projects and happier data scientists.