Did you know CAN's blog is full of sound data science related advice dating back to the beginning of CAN? In case you didn't, we make it a habit to regularly re-post our favorites. What follows are reasons why you should consider becoming a data scientist. If it grabs you - check out the Omaha Data Science Academy. It might be the first step in your data science career.
Why Become a Data Scientist?
Too few of today’s college students realize they want to be data scientists when they graduate. We believe that data scientists are the future, and that we are on edge of a data science revolution. Therefore, we decided to explain why to become a Data Scientist.
1. As a data scientist, you have incredible access across the business.
Your job of modeling specific business strategies and forecasts requires you to have broad access across your company. People look to you to bridge the gap between business theory and relevant data.
This is a tough role because it requires you to develop and implement a strategy to create consensus in order to implement the results of your work. Since the days of the English Luddites (the anti-technology loom weavers) there have been people who are against technological progress and the efficiency it brings to the economy. The best data scientists will be able to manage the political and social change that comes from their work. Data Science success isn’t only about making work more productive, it is also about helping other people adjust and succeed.
2. Being a Data Scientist is a specialized field.
The requirements to be a data scientist are long, because the decisions they make impact thousands of people. Data scientists usually have a 3.5 GPA or higher. They must have the ability to learn and share several different forms of knowledge, including principles of computer science, high business acumen, and complex math. Learn more about how to become a data scientist.
3. You have the opportunity to work with top level management extremely early in your career.
While this sounds great, it is also challenging. You need to be comfortable giving board room presentations to people who don’t understand what you’re talking about. A specific aspect of your position is to clearly articulate why your results are useful and valid — and do it without math speak. Learn more about presenting business intelligence.
4. The best data scientists never settle, and question everything.
Whereas a statistician starts with a data set and a problem, a data scientist has a more difficult task. A really great data scientist will constantly ask, “are we solving the right problem?” Often the perceived problem won’t match your data, requiring you to look at everything from a new perspective.
A data scientist spends his energy asking machines questions and then trying to validate the answers, instead of spending energy trying to address the question directly. This requires a different work process, one that requires humility and understanding. Data scientist know while they are the ‘go to’ person in the organization, they don’t have all the answers. However, at the end of the day they are still responsible for finding the answers, which is why they get paid the big bucks. Data Science is a complex science as opposed to a simple science.
5. You use artificial intelligence to automate the most routine, frustrating jobs known to mankind.
Instead of doing routine tasks, you can be responsible for automating the most tedious aspects of business, while saving your customers money and making enterprise more efficient.