This economy has made many people consider their career choices. If you are looking for job security and decent pay, you might want to consider a career in computer science. Jobs in technology will be in demand for a long time, and many companies pay well for these skills. Computer science is an especially attractive option for those who have an affinity toward technology. However, there are a number of different career paths available. Two popular options include data scientist and software engineer. Learn more about the two different vocations and which one is right for you.
Data Science
Data scientists use technology to analyze and assess data and then apply the information to make operational suggestions or use the information to earn the company more money.
The data received can be as simple as customer demographics, such as age, gender, income level, and more. This information can be used to adjust marketing campaigns. It can also be monetized by selling the data to other companies. However, most companies want more data than simple demographics. Therefore, they will need to use systems that collect more data from users.
Some of the skills required of a data scientist include:
– Mathematics and statistics
Data analysts need to quantify the data they ascertain to make sense of it. They will also need to understand how to read statistics to see how the data compares to similar data sets.
– Programming (Python and R)
Data analysts should know basic programming, such as Python. While they don’t typically need to program new software, they may need the programming software to properly collect and analyze information.
– Data visualization and analysis
Arguably the most important skill required of a data analyst is the ability to organize and analyze data. It’s not enough to simply write down the numbers; you need to know what the figures mean.
– Advanced communication skills
Once you analyze data, you need to be able to present your findings to the proper authorities in a way that makes sense to them and apply the findings to the company.
Software Engeneering
A software engineer develops systems to facilitate business practices. They will develop the code to create proprietary systems that give an organization a competitive edge. They can also examine a company’s current software to determine which upgrades can provide the best return on the investment.
Software engineers also need to test software to find weaknesses and fix them. Users may not be able to perform their duties at peak efficiency if they are limited by technical errors.
Skills required as a software engineer include:
– Math, science, engineering, and design techniques
programmers need to know engineering and design on top of math and science. Engineering gives them the skills to create something that works, and design skills make the creation user-friendly.
– Advanced analytical and problem-solving skills
When something goes wrong with beta software, it requires advanced problem-solving to get to the bottom of the problem.
– Fluency in one (or more) computer coding languages
Programmers must be able to code in several different languages, as certain situations may require different program languages.
– Attention to detail
Coding is extremely detailed. One small error can impact the entire program. Therefore, it’s important to have a strong attention to detail.
Data Analyst vs Software Engineer: What’s the difference?
The main difference between a data scientist and a software engineer is their point of entry into the conversation. A software engineer enters the conversation early in the game, helping to establish technical systems and software for an organization, while a data analyst enters the conversation after the fact to learn what they can from the systems put in place by the software engineer.
Data analysts will use data scientist software to perform their job, while software engineers are the ones creating the programs.
While the salary is relatively similar, there is also a difference in salary. The national average salary for a data analyst is $120,306, while the national average salary for a software engineer is only $101,760. With that being said, it’s important to note that the salary depends on the level of training and experience. Supervisory roles will earn more than entry-level roles.
How to Transition from Data Science to Software Engineer
To transition from data science to software engineer, you need to get the proper training. You may want to go back to school to learn more coding if that isn’t your strong suit. You will not only need to be able to code, but you’ll need to be able to code in multiple different languages.
Some of the popular coding languages include:
– Javascript
– Java
– Python
– C#
You will choose the language you decide to learn based on your knowledge level and industry. Certain languages, such as Python and JavaScript, are better for beginners. After you have a strong handle on the beginning-level languages, you can graduate to intermediate and advanced programming languages.
After you learn how to code, you can implement said code into your current role as a data analyst. Examine your current software to find areas where you may be able to add code to make the process more effective or more efficient. This will give you experience in altering software. After you feel comfortable working with existing software, it’s time to create your own software.
You can start with data science software development to become a data software engineer. Soon, you can look for a job with a data science consulting firm.
Conclusion
Technology is the way of the future. Therefore, a job in computer science is a pretty safe bet. There are two main components of computer science: software development and data analysis. Both careers offer respectable salaries. However, these are two very different jobs. You may be able to start your career as a data analyst and then transition to a job in software development by overlapping some skills and developing new ones.
