IEEE Computer Society Team<\/p>\n<\/p><\/div>\n
![\"man](\"https:\/\/ieeecs-media.computer.org\/wp-media\/2022\/04\/04220052\/Data-Scientist-or-Software-Developer-How-to-Choose-Which-is-Best-for-You.jpg\")
Are you an engineer looking for a career change or a new grad looking for your first job? If so, the emerging field of data science is a career that should be on your radar. Data science is an emerging and high-paying field that is in demand across the board at large companies and government agencies. Given our society\u2019s increasing dependence on large amounts of data to make actionable decisions, the need for data scientists isn\u2019t going away any time soon. The market penetration of data science is nearly universal. Any entity that collects significant amounts of data is using data scientists to process and analyze it.<\/p>\n
Whether you\u2019re an electrical, computer, or software engineer, the good news for engineers is that data science leverages many of the skills you already have. As a result, it\u2019s a great choice for a career change whether you\u2019re fresh out of school or a well-seasoned engineer with years of experience.<\/p>\n
\u00a0<\/p>\n
\n
\u00a0<\/p>\n
Want More Career-focused News? Subscribe to Build Your Career Newsletter Today!<\/strong><\/p>\n \u00a0<\/p>\n \u00a0<\/p>\n Data science is a relatively new interdisciplinary field that arose from the need to analyze the massive amounts of data that corporations and governments collect as a part of their ordinary business. Ultimately, the goal is to detect and analyze hidden patterns in the data, using these patterns to predict future behavior and detect trends. Actionable insights could include anything from creating targeted marketing campaigns to detecting the existence of a terrorist network that may be planning an attack. Anomaly detection using extensive data sets is an important task in data science.<\/p>\n Data science relies on the most up-to-date technology, using artificial intelligence, machine learning, statistics, and other tools to achieve its goals. Software development experience and deep knowledge of probability and statistics are important for anyone looking to move into data science. Visualization of data, integration of data from multiple sources, analysis and interpretation of data, working with and analyzing complex systems, and a mathematical background are all essential skills for a data scientist. Knowledge of parallel and distributed systems is also important for a career in data science.<\/p>\n \u00a0<\/p>\n The good news for software, electrical, and computer engineers is that most will have an educational background and work experience that could make them suitable for a career in data science. Most engineers with expertise on the job have worked with at least some of the tools used in day-to-day work by data scientists. These include Matlab, R, and Python programming languages. Knowledge of statistics is critical and a background in neural networks, while not required, is a big boost.<\/p>\n For engineers that are not sure about their suitability for a career change to data science, further education might be in order. Those looking to gain a competitive edge might consider getting a degree in statistics, but that\u2019s not necessary for most. However, if you lack knowledge of any of the core areas in data science, taking a few key courses could improve your odds of landing a high-paying position. Advanced coursework in statistics and probability can be an important resume enhancer. In particular, look for the opportunity to use a software package used in statistics. In addition, seek out courses in Python to enhance your software development background if you don\u2019t have Python experience already. If you don\u2019t have a background in neural networks, getting some academic exposure to this important niche will give you an edge when seeking new employment.<\/p>\n \u00a0<\/p>\n More articles that might interest you:<\/strong><\/p>\n \u00a0<\/p>\n To find out if a career change from engineering or software development to data science could lead to a higher income, we consulted Glassdoor. The website tracks salaries across nearly every occupation. Looking at the average base pay in Denver, Colorado, it\u2019s clear that the high demand for data scientists pays off.<\/p>\n While the average base pay for electrical and software engineers in the Denver metro area is $89,587 and $96,624, respectively, a data scientist in the Denver metro area can expect an average base salary of $117,890. That\u2019s a boost of about 22% in base income for a software engineer living in the Denver area. Keep in mind that these figures are not based on scientific surveys but rather on self-reported salaries.<\/p>\n \u00a0<\/p>\n There will always be a need for software developers and engineers, and while the current job environment is pushing salaries of data scientists higher, as supply and demand meet the salaries of software engineers and data scientists are likely to move closer to each other. However, data science is a new and growing field that is in demand nearly across the board, from advertising agencies to homeland security \u2013 so growth in the field is not going to end anytime soon.<\/p>\n If you are ready to seek out new challenges and are looking for a career change that utilizes existing skills, data science offers an opportunity for a high-paying, in-demand, and exciting, a fast-moving field that uses your skills and the latest technology. Check out IEEE Computer Society\u2019s job board to take a look at options today, and check out the blog to stay up-to-date on all tech news!<\/p>\n<\/p><\/div>\n
\nWhat is Data Science, Anyway?<\/h2>\n
\nAre Engineers and Software Developers Well Suited for a Career Change to Data Science?<\/h2>\n
\nHigh Demand Means Data Scientists Make More on Average<\/h2>\n
Which is Better for Long-Term Growth?<\/h2>\n
\n