Beginner Python & Math for Data Science Starts Monday! Enroll Now

Sr. Data Scientist Roundup: Effects of AI Bias, Impact Hypothesis, and Tips for Hiring Your Data Team

By Emily Wilson • March 26, 2019

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.

Sophie Searcy, Metis Sr. Data Scientist 

As Women's History Month comes to a close, we take a look at Biased AI Is Real: What Does That Mean for Women? – a new article by Metis Sr. Data Scientist Sophie Searcy, published in InformationWeek. 

"We have a great opportunity to lay a better foundation for the future of AI if we encourage more women and people of diverse backgrounds to dive into data science and other AI fields," she writes. "And those of us already on the front lines should use this time to think about how we’ll fight against bias in our own domains. The AI revolution is set to change the world; let’s make sure it’s for the better." 

Dig into the full article here

Kerstin Frailey, Metis Sr. Data Science - Corporate Training

Too often we assume that good data science translates to effective data science, even though it's untrue, according to Metis Sr. Data Scientist Kerstin Frailey. In her latest blog post, she writes about The Impact Hypothesis, which she considers the "keystone to transformative data science." In essence, the hypothesis explains how to critically scope and communicate how a project will drive impact for your business, ensuring both good and effective data science occurs. 

Read the post here.


Brendan Herger, Metis Sr. Data Scientist - Corporate Training

As data continues to change the way companies do business, the task of attracting (and retaining) data science talent can be difficult. In his latest blog post, Metis Sr. Data Scientist Brendan Herger draws from years of experience to provide a playbook for how to effectively and efficiently hire data scientists and build out your team.

Check out the Playbook here.

__________

What were our Sr. Data Scientists up to last month? Find out here.


Similar Posts

data science
Sr. Data Scientist Roundup: Managing Essential Curiosity, Creating Function Factories in Python, and Much More

By Emily Wilson • February 22, 2019

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.

data science
Sr. Data Scientist Roundup: How WaveNet Works, Art + Data Science, Upcoming Conference Talks, & More

By Emily Wilson • June 19, 2019

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 science
From Intro to Data Science Grad, to Bootcamp Grad, to Data Scientist: A Q&A with Renkoh Kato

By Metis • January 30, 2019

When we refer to Renkoh Kato as a "Metis graduate," we mean it in multiple ways. He first graduated from our part-time Introduction to Data Science course before applying to and graduating from our full-time Data Science Bootcamp. He's now a Data Scientist at JPMorgan Chase. In this post, read a brief Q&A about his journey from Intro student, to Bootcamp student, to Data Scientist.