I’ve spent many years fighting against the label of “data scientist” because I’ve always thought it did a poor job of representing what is actually done on the job. I love the idea of the “data hacker” as I describe here. But alas… There’s not much I can do to stop this train now.
What is Data Science?
Data science is a nuanced discipline where a mix of many different areas of expertise are required to be successful. This includes probability & statistics, machine learning, data visualization, computer programming, communications, and a large dose of curiosity.
These specialties are brought together to paint a clear picture of what has happened, is happening, or will happen with a process or system of interest.
If you’re curious about what some of these areas are, take a look here:
- What is Probability & Statistics? – In Progress
- What is Machine Learning?
- What is Data Visualization? – In Progress
Why Should You Care?
There are many reasons data science should be of interest. From a career perspective, it has been called one of the “sexiest” jobs of the 21st century by Harvard Business Review and is currently ranked as the #3 best job in America by Glassdoor. This is largely because data scientists are in demand across many major industries (not just tech) and get paid handsomely for their efforts. There’s a great article with some worthwhile highlights from KDnuggets if you’re interested in reading more about data science as a career.
If that’s not enough, data science is shaping how we interact with the world. Spam gets shuffled off to the trash, you can talk to your TV or phone, get recommendations for movies to watch, stay safe on the road, find the best route home, and more all because of machine learning and the data scientists behind these innovations.
Next Steps
If you want to take steps to improve your data science chops, regardless if you’re just starting out or a seasoned pro, the Data Science BS Series is a great place to start. Each article tackles one topic related to probability & statistics, machine learning, or data visualization. Posts are kept intentionally brief (a 5-15 minute read) and will often include coding examples which can all be found here.