Data science

Data sciences combines

scientific methods
statistics (some equate statistics with data science!)
Data analysis
machine learning
Classification and prediction
Clustering
uncertainity quantification
computional science
Artificial Intelligence
Data-mining
Database technologies
Visualization
processes
algorithms
systems

Process

Collect data
Clean data
Exploratory data analysis
Create models and algorithms
Test algorithms
Make predictions
Communicate results (visualization)
Repeat and improve

Skills

A data scientist has the following skills:

Likes data, obviously. This includes preparing data (ETL etc.) and crunching numbers
Curious - so that he explores and researches new algorithms, techniques and paradigms
Is a good software developer - so that he can implement the algorithms in modern programming languages.
Understands software architecture - so that he can build sophisticated big data environments
Good communicator - so that he can explain and present the distilled result (insights) to stake holders.

Arguably, the most fruitful skill as a data scientist is the ability to clean data: it saves hours of time and makes it easier to visualize data and draw conclusions from it.