Depending on who you ask, data science is a new and evolving field that combines the use of statistical analysis, predictive modeling, and machine learning, all of which is built on a solid foundation of business acumen.
Some will claim they've been a practicing data scientist for decades, long before the term even existed. They're probably right. The reality is that data science is a broad term used to describe a field that is continually growing, nearly as fast as data itself. However, the important thing to remember is that whether the title is broad or specific, a data scientist is someone who is able to evolve with growing demands. A data scientist is someone who is comfortable with the unknown, who is comfortable with the idea that there may not be a solution readily available, who pushes forward nonetheless.
A data scientist must rely on technical expertise, sophisticated modeling techniques, and proven engineering methodologies to gain insight. More importantly though, a data scientist must rely on his ability to understand the nuances of the data and to navigate the ever-changing need to balance analytical rigor with actionable insight.
In short, data science is the marriage of mathematical modeling and business intelligence, with just a touch of art to round it all out.