In a world that’s increasingly reliant on technology, data scientists are pioneers of technological change across a huge array of industries. They solve modern problems, analyze trends, and extract meaning from large and complex sets of data. As a growing number of companies commit to data-driven development, and as they collect and compile more information via the internet, there’s ample opportunity for data scientists to flex their analytic skills and computer science abilities.
In this position, individuals integrate advanced IT knowledge with other proficiencies — from communication and data visualization to algebra and programming — to interpret various sets of data. They then apply the information they glean to the development of creative, evidence-based solutions with wide applications. You’ll find data scientists working in fields as diverse as biotechnology, energy development, transportation, and telecommunications.
What data scientists do varies depending on their specific training, interests, and where they focus their careers. Regardless of field, these professional data wranglers are vital in today’s technology-driven, solutions-oriented world. Those interested in learning how to become a data scientist can take a few steps to prepare to pursue a role in this dynamic field.
Data Scientist Job Description
Data scientists need to consider the nuances of structured and unstructured data, while also applying skills gained through the study of statistics and machine learning. As they clean, combine, and consider the numbers, data scientists strive to eliminate any biases in the data, with the ultimate goal of extracting meaningful information, which they can then put to use.
This field requires persistence, curiosity, and a desire to uncover the hidden meaning in a wealth of raw material. What data scientists do is complex and often varies by position. That being said, there are a few key tasks common to most data scientist job descriptions.
For instance, problem identification is an essential task of the profession. Data scientists frequently work with others at a business or organization to either identify a problem or formulate a question. After determining this vital jumping-off point, they can then consider how to approach finding a solution through data science.
Another core responsibility involves the collection and organization of large datasets. Once data scientists understand the variables and what information they’re looking for, they can consider how to approach collecting the data, which can often come from multiple sources. They might formulate algorithms, model experiments, or otherwise conduct research to get to the heart of the problem and provide a solution.
The collection of data leads to another primary task — data analysis. It’s up to the individuals to call upon data scientist skills to analyze the data, whether it’s been personally collected or provided by a secondary source. They determine the correct sets to work with, validate data accuracy, and identify patterns.
Finally, it’s up to the data scientists to interpret the data to find solutions and opportunities. They communicate their findings to their audience, whether that audience is an organization’s stakeholders or the public. This interpretation is then used by businesses to make vital decisions.
Data Scientist Salaries
Data scientists are in high demand today for their ability to design creative, data-driven approaches to real-world problems. This work’s value is reflected in the average salary of a high-level data scientist. Individuals with a master’s degree in the field earn a median annual salary of $118,370, according to the U.S. Bureau of Labor Statistics (BLS).
While data science is generally a lucrative profession, data scientist salaries can vary. Pay often depends on the industry, level of experience, level of education, workplace environment, and region. It’s also worth noting that those pursuing a role as a data scientist are entering an in-demand field. The BLS projects a 16% increase for computer and information research scientist roles, such as data scientists, between 2018 and 2028. This represents a much higher rate of growth compared to the 5% increase that the BLS projects for the typical profession.
Career Path for Data Scientists
When considering how to become a data scientist, be aware that you’ll likely need to take some steps before finding work in this growing, information-driven field. Most people who pursue the career path for data scientists start engaging with the concepts through both formal education and hands-on, independent practice. It’s helpful for aspiring data scientists to possess an interest in programming and complex systems from the outset. In addition, most students complete the following steps before landing a position as a data scientist:
Step One: Complete an Undergraduate Degree
Many people get their start on this career path by earning an undergraduate degree in data science. This foundational degree generally provides a background in information technology, mathematics, computer science, and statistics. Each of these disciplines speaks to some of the skills required for the data scientist role.
Step Two: Gain Experience with an Entry-Level Job
Getting experience in the field is important in most professions, and data science is no exception. Most people find that it’s useful to spend a few years post-graduation flexing their programming and analytical skills on the job. As a junior data scientist, you’ll have the chance to get specific, hands-on training, and you’ll gain a deeper understanding of what it takes to work at a high level in the field.
Step Three: Pursue a Master’s Degree
The data science field tends to afford more opportunities to those with advanced degrees. Continuing your education at a graduate level allows you to learn more about important topics that are valuable in an upper-level position, such as predictive analytics and model building. By gaining advanced knowledge in a program such as an online master’s in data science, you can prepare to advance your career in data science.
Step Four: Never Stop Learning
Technologies change fast, and so do the needs of organizations that employ data scientists. If you want to become a data scientist, you must cultivate a desire to continue your education in the field. In this ever-evolving sector, the drive to always learn and grow will help you stay competitive in the job market and engage with the dynamic world of data.
Learn More About the Path to Data Science Careers
If you’re looking to advance or shift your career, consider an advanced degree in the field of data science. An online master’s degree in data science from Maryville University can equip you to help companies and organizations leverage data and technology to make critical decisions. Discover how to begin your journey to a rewarding career.