Data Scientists, You’re Invited: Make 2022 a Year of Continuous Improvement
Join renowned surgeon and author, Atul Gawande, and J&J’s Chief Data Science Officer, Najat Khan, for a special event on driving exceptional performance.
In some domains, good enough isn’t good enough; exceptional performance is required every time.
Doctors know this situation well, as every decision they make can have life-altering consequences.
Increasingly, data science is one of these fields. It’s a discipline in which small differences in performance can have a massive impact. Slight modeling improvements can drive millions of dollars of incremental revenue. Small mistakes can result in colossal losses.
Join Domino Data Lab for a special virtual event on January 26 to learn how to unleash exceptional performance through continuous improvement in 2022.
Register for free today to hear from:
Atul Gawande, one of the most influential voices in healthcare
A renowned surgeon, bestselling author, and performance improvement expert, Dr. Gawande will share his insights from years of driving continuous improvement inside hospitals. You’ll learn how coaching, checklists, and best practices can power exceptional performance.
Najat Khan, Chief Data Science Officer at Johnson & Johnson
Najat Khan will share her perspective on continuous improvement at the intersection of medical research and data science. In her transformative role leading data science at Johnson & Johnson, Dr. Khan will bring frontline insights at a time when the work of teams like hers is benefitting billions of people around the world.
The lessons of Atul Gawande and Najat Khan will come together as Nick Elprin, CEO of Domino Data Lab, connects them to data science and the concept of model velocity. Maximizing model velocity means achieving near-continuous performance improvement in a model-driven business.
To support companies looking to accelerate model velocity, Elprin will also reveal Domino 5.0, a major step forward in Domino’s mission to help businesses unleash the power of data science.