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Demystifying Data Science Recap: Breaking Down Hilary Mason's Keynote

By Emily Wilson • August 26, 2019

In July, we hosted our 3rd annual Demystifying Data Science live online conference. On Day 2, we offered 8 talks and 3 workshops filled with content geared toward an audience of Data-Focused Business Leaders and Practitioners. We couldn't have asked for a better way to start the day than by hearing a keynote talk from Hilary Mason, General Manager of Machine Learning at Cloudera. Read a recap of it here + get access to the recording for free.

business resource
Demystifying Data Science Day 2 Content: For Business Leaders & Practitioners

By Metis • August 21, 2019

Last month, we had the pleasure of hosting our 3rd annual Demystifying Data Science live online conference. Day 2 was filled with talks and workshops geared toward an audience of Data-Focused Business Leaders and Practitioners. In this post, we'll briefly recap what happened on that day, including who spoke, what they discussed, and how you can access every recorded talk and workshop for learning on your own time.

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How Complicated is the Data Science Population? A Comprehensive Look at IBM, McKinsey, & LinkedIn Reports

By Metis • July 30, 2019

In this guest post from IADSS, read about extensive research being done with the goal of proposing industry standards for the data analytics profession.

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Financial Applications of Natural Language Processing

By Adam Wearne • June 25, 2019

In an increasingly competitive financial landscape, gaining an informational edge is vital to constructing and maintaining a superior equity portfolio. Alternative data sources including satellite images, sensor data from IoT devices, text, and video are all becoming increasingly important sources of insight for active equity strategies. In this post, Metis Sr. Data Scientist Adam Wearne, explores some of the common Natural Language Processing (NLP) techniques that are used in asset management.

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Burtch Works’ 2019 Data Science Salary Report Shows Current Market Trends

By Linda Burtch • June 24, 2019

Market data on data science and analytics professionals is exceedingly scarce. Burtch Works, the leading executive recruitment firm, has released annual reports to share insights from the unique vantage point of recruiters that interview thousands of quantitative professionals and hundreds of teams every year. This year, for the first time, they've combined their separate Data Science and Predictive Analytics salary reports into one.

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Metis Case Study: Helping CMA Consulting Remain on the Cutting Edge

By Metis • May 24, 2019

In this case study, read how we worked with CMA Strategy Consulting (a boutique consulting firm focused on the telecommunications, media, and high tech industries) to evolve its capabilities and ensure its services remained on the cutting edge.

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Scoping a Data Science Project

By Damien Martin • April 22, 2019

In February, Metis Sr. Data Scientist Damien Martin wrote a post on how to foster a data literate and empowered workforce, which allows your data science team to then work on projects rather than ad hoc analyses. In this post, he explains how to carefully scope those data science projects for maximum impact and benefit.

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Why You Should Consider Outsourcing Your Next Training Project

By Douglas Noll • April 19, 2019

If you’ve ever been responsible for, or had a degree of influence in, building a training program for your organization, you’ve likely been faced with a potential dilemma: Can you build the training in-house, or do you need external assistance via a training partner? In this post, read the case for the latter.

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Playbook: Hiring Data Scientists

By Brendan Herger • March 25, 2019

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.

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The Impact Hypothesis: The Keystone to Transformative Data Science

By Kerstin Frailey • March 22, 2019

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.

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Metis's Michael Galvin Talks Improving Data Literacy, Upskilling Teams, & Python's Rise with Burtch Works

By Metis • February 27, 2019

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.

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Democratizing Data: How Training Your Team Leads to Better Projects & Happier Data Scientists

By Damien Martin • February 20, 2019

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.

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Rabbit Holes, Red Herrings, and Rewards: Managing Curiosity

By Kerstin Frailey • January 28, 2019

Curiosity is essential to good data science. It’s one of the most important characteristics to look for in a data scientist and to foster in your data team. Despite that, curiosity is rarely directly managed. In this post, Metis Sr. Data Scientist Kerstin Frailey dives into how you should approach it.

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Playbook: How to Successfully Launch a Data Science Team

By Brendan Herger • January 23, 2019

The word 'pioneering' is rarely associated with banks, but in a unique move, one Fortune 500 bank had the foresight to create a Machine Learning center that helped keep it from going the way of Blockbuster. Metis Sr. Data Scientist Brendan Herger was fortunate to co-found this center, and in this post, he shares some insights, particularly as they relate to successfully launching a new data science team within your organization.