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How To Ace The Data Science Interview
By David Ziganto • July 25, 2017

There’s no way around it. Technical interviews can seem harrowing. Nowhere, I would argue, is this truer than in data science. There’s just so much to know. What if they ask about bagging or boosting or A/B testing? What about SQL or Apache Spark or maximum likelihood estimation? Sr. Data Scientist David Ziganto provides 7 must-read tips for acing your next interview.

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Displaying Images in Tableau (with some help from Python)

By Roberto Reif • July 24, 2017

With Tableau, one of the cool things you can do is define every pixel from an image. This allows you to create interesting visualizations as described in this blog post by Sr. Data Scientist Roberto Reif.

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Demystifying Data Science: Grad Works On Cutting-Edge Self-Driving Car Technology

By Metis • July 24, 2017

Self-driving cars, once only existent in the realm of science fiction, edge closer to reality with each passing day. Data scientists like Galen Ballew, a graduate of the first Metis bootcamp in Chicago, are working day in and day out to make it so.

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Demystifying Data Science: From Startup to Big Business, Being Leveraged Effectively On The Job

By Emily Wilson • July 17, 2017

This role is different for Andre Gatorano – and that’s a good thing. He’s now a Principal Data Scientist at Capital One, where he enjoys the fruits of the company’s noticeably strong commitment to a comprehensive data strategy.

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Faster Python - Tips & Tricks

By David Ziganto • July 14, 2017

There is a plethora of information about how to speed up Python code. Some strategies revolve around leveraging libraries like Cython, whereas others propose a “do this, not that” coding approach. There exist many “do this, not that” strategies but I decided to focus on just a few. This post is split into two parts. In Part 1, I will compare two approaches commensurate with the “do this, not that” logic to see if there is a substantial difference and, if so, which approach is better. In Part 2, I will compare Python 2 and Python 3 to see if there is credence to the claim that Python 3 is indeed faster.

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Demystifying Data Science: The Push to Keep Learning Leads to a New Career

By Emily Wilson • June 26, 2017

Bootcamp graduate Kimberley Mitchell, now a Data Analyst at Newsela, always had a significant interest in one crucial pillar of data science – statistics. This propelled her toward degrees in industrial engineering and economics, and into a career that has clear a delineation between before and after the birth of the mainstream internet. She worked as a Quality Engineer for AT&T and as a Statistician for Universal Instruments, among other roles, before the web took off and she wanted to take off with it.

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Demystifying Data Science: A Math-Loving Hip Hop Fan Becomes an Expert at Spotify

By Emily Wilson • June 20, 2017

For Emily Hough-Kovacs, it’s not just about the final product when it comes to music. It’s about the intricacies of production, the record label, and the entire creative and business process. Now a Data Scientist at music streaming giant Spotify, she works on the Creator Products Insights Team.

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Demystifying Data Science: Exploring the Intersection between Medicine and Data Science

By Metis • June 08, 2017

This post was written by Sameh Saleh, Metis Data Science Bootcamp graduate and current Resident Physician in Internal Medicine at UT Southwestern Medical Center. He shares his story with the hope to inspire other clinicians-in-training to seriously consider the value of a data science education in their lifelong medical endeavors.

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Demystifying Data Science: Professional Poker Player Turned Data Scientist at FanDuel

By Metis • June 07, 2017

Before he’d even heard of data science, Andy Sherman-Ash was employing the powers of artificial intelligence in his career as a professional poker player. He taught himself how to code by crafting a neural network-based poker AI that used the machine learning software Weka.

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Demystifying Data Science: A Passion for Academic Research Leads to Data

By Metis • June 06, 2017

The road to a career in data science is often unpaved and unpredictable. For Metis alumna Jessica Cox, it started with a bachelor’s degree in biochemistry and led to her current role as Data Scientist at Elsevier Labs, a scientific publishing company. During her undergraduate studies, she realized how much she adored research. She followed that passion through to a Ph.D. in Biomedical Science, focused on environmental health and nutrition research. That’s when another life-changing realization hit her: she loved data.

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