Blog

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.

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.

By Douglas Noll • June 19, 2019

If you’ve ever led or were responsible for putting together a data science and analytics training project, you know it can be a difficult and time-consuming process. But putting a training project plan in place doesn’t have to be difficult as long as you’re keeping a few key steps in mind along the way.

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.

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.

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.

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.

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.

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.

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.

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.

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.