Subject archive for "enterprise-mlops," page 2

Last week Domino celebrated data science innovators driving breakthroughs in health and life sciences. This week we announce a new slate of innovators in the Financial Services and Insurance edition of the Data Science Innovator’s Playbook, available now as a free download. As before, each of its top data science innovation leaders in the financial services and insurance industries share insights on their work, careers, and the data science profession. The playbook includes seven profiles, the first being of Dr. Tiffany Perkins-Munn.

Today's most successful organizations put AI and machine learning models at the heart of their business, creating competitive advantage by accelerating innovation, improving customer experience, and making faster and less-biased decisions. Data science teams building AI-driven applications and experiences require flexible access to the latest tools and any data across hybrid, multi-cloud and on-premises environments. Success with building models that drive digital transformation also requires the security, governance, and compliance that enterprises and governments expect regardless of the underlying infrastructure.

If you’re working in data science and are feeling like making a job change, here are some things top data science innovators say to consider as you look for a new opportunity or plan your next career move. Their career advice–and much more–is captured in the new ebook, The Data Science Innovator’s Playbook, from Domino Data Lab.

What if you wanted to do something really ambitious in data science–something like designing an innovative new search engine? Today, that would be a daunting task, and you’d probably need a big, highly qualified team of data scientists and programmers to bring your innovation to life. And you’d need months, if not years, to finish it.

What if machine learning and data scattered around the world held the keys to the cures for a variety of rare or new diseases? Until recently, it was often nearly impossible to use that data, due in part to the data privacy restrictions in place around the world. That’s starting to change, thanks to federated learning and the innovative work of doctors such as Mona Flores, head of medical AI at NVIDIA.

How do you build a data science capability into a powerful force for making decisions about virtually all facets of your business? And how do you recruit, train, organize, and retrain members of your team, in a field where competition for talent is intense and growing? These are just a couple of the questions that Glenn Hofmann, chief analytics officer at New York Life Insurance Company, has confronted and mastered in his tenure there.