1. What’s in a Successful Data Scientist
Chapter 1 from How to Lead in Data Science by Jike Chong and Yue Cathy Chang
This chapter covers
- Learning about data scientist expectations
- Examining career progression challenges of data scientists
Data science as a field is driving a quantitative understanding of the world around us. With today's technical capabilities to aggregate large quantities of data paired with inexpensive computing resources, data scientists are discovering patterns through analysis and modeling at a scale that was not possible before. This quantitative understanding is being used to predict the future and drive critical business decisions. While predictions may or may not be accurate at first, they can be validated and improved upon through various techniques such as controlled experiments, time series windowing, and reinforcement learning. This scientific process to validate our understanding and predictions of the world enables more accurate analysis and models to be built over time.
Leadership is the ability to amplify one’s capabilities through influence, supervision, governance, and inspiration to produce more significant impacts than what can be achieved as an individual. There are opportunities to lead as a technical individual contributor or as a people manager.