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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 orcorporate trainingcourses, they're working on a variety of other projects. This monthly blog series tracks and discusses some of their recent activities and accomplishments.
"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."
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.
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.
Data scientists are often described as hybrids: part statistician, part computer scientist; part analyst, part strategist. But while we focus on the myriad technical skills that a data scientist should possess, we often overlook one of the foundational skills (without which the whole edifice falls apart): communication skills. In this post, read three tips for improving your professional communication skills.
This post from Metis Sr. Data Scientist Kimberly Fessell covers the basics of object detection: what it is, various approaches to it, the measurements used to judge its results, along with a few important considerations of modern object detection.