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.
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.
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. This post 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.
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.
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.
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.