The expertise in data science can only expand more, given the multiplicity of global affairs and our growing reliance on ever evolving technology.
Data Science has become a breakthrough technology that everyone is talking about. By selecting Data Science as a profession, millions of professionals have ensured their future in recent years. By obtaining a degree or a course in Data Science, you can begin this career.
The expertise in data science, e.g. big data, artificial intelligence, machine learning, etc., can only expand more, given the multiplicity of global affairs and our growing reliance on ever evolving technology. You are in a safe position to retain the reputation that comes with being an outstanding data scientist, at least for a few decades from now.
According to Northeastern University, “For four years in a row, data scientist has been named as the number one job in the U.S. by Glassdoor. What’s more, the U.S. Bureau of Labor Statistics reports that the demand for data science skills will drive 27.9% rise in employment in the field through 2026. Not only is there a huge demand, but there is also a noticeable shortage of qualified data scientists.”
Data scientists work closely with business stakeholders to understand their goals and determine how data can be used to achieve those goals. They design data modeling processes, create algorithms and predictive models to extract the data the business needs, and help analyze the data and share insights with peers. While each project is different, the process for gathering and analyzing data generally follows the below path:
1. Ask the right questions to begin the discovery process
2. Acquire data
3. Process and clean the data
4. Integrate and store data
5. Initial data investigation and exploratory data analysis
6. Choose one or more potential models and algorithms
7. Apply data science techniques, such as machine learning, statistical modeling, and artificial intelligence
8. Measure and improve results
9. Present final result to stakeholders
10. Make adjustments based on feedback
11. Repeat the process to solve a new problem
The most common careers in data science include the following roles.
Although the roles of data scientists and data analysts are often conflated, their responsibilities are actually quite different. Put simply, data scientists develop processes for modeling data while data analysts examine data sets to identify trends and draw conclusions. Because of this distinction and the more technical nature of data science, the role of a data scientist is often considered to be more senior than that of a data analyst; however, both positions may be attainable with similar educational backgrounds.