Data science underlies much of what we see around us. Data drives recommendations for movies and TV series. Every time you thumbs-up a streaming song, you’re adding to the database algorithms used to make future recommendations. Trucks and trailers outfitted with smart sensors provide a flood of information that managers use to plan routes, schedule maintenance and reduce fuel costs. Airline pricing decisions, new product development and self-driving cars all benefit from the work of data scientists. 

All of these systems are driven by the work of data scientists, who turn raw information into useful insights. Data science can help the development of machine learning and artificial intelligence, transforming the way companies conduct business. If you are interested in working in this exciting field, read on about how to become a data scientist.

There is so much data in the world, it would be hard for an average person to gather, sort, analyze and interpret it. Data scientists are trained to help organizations answer questions about past performance and gain insights on future trends. At its core, data science is about finding meaning in masses of data.

Keep in mind that data science is a different field than statistics. While they may seem similar and may use some of the same techniques, data science is more engaged with technology. Classic statistical methods predate the computer age and are still in use. Data science relies on computers to sort data and run algorithms that create models of predicted behavior based on past experiences. The science part of the equation comes into play by using a type of scientific method to test and refine algorithms and data models. There may be dead ends and errors, but every bump in the road is useful in homing in on the answers you seek. The data scientist should be willing to think of what others may see as a failure as a learning experience.

A data scientist should be curious about the world around them and be willing to solve problems. Why become a data scientist? There are plenty of reasons, ranging from curiosity to job prospects. 

The process to become a data scientist can be a lifelong journey. A common first step is to earn a bachelor’s degree in a relevant field. Some earn a master’s degree in data science to possibly improve career positions and salary. A Ph.D. is another option in this field to help achieve the goal of an advanced leadership position. The journey to become an advanced data scientist could take eight to 10 years or more to earn different degrees. If you simply want to shore up your skill set rather than obtain a full degree, there are also individual data science courses and certificates you may pursue.

A solid education is a foundation for success as a data scientist. Because there’s such demand for data scientists and mathematicians, employers may look to hire data scientists with excellent credentials.

A four-year degree is often the starting point to launch a career in data science. However, the undergraduate degree may not be in data science. Those kinds of degrees may not have been an option for you if you’ve been out of undergrad for a few years.

Common degrees that provide a foundation for data science include

If you’re looking for a bachelor’s degree program, choose one that offers a range of courses in statistics, computer science and analytical techniques. Training in making business judgments grounded in data will also be useful. Depending on your career goals, a master’s degree in data science could prepare you for the next level.

A four-year degree offers structure and discipline in the academic area, with a widely recognized credential. You can also benefit from internships, alumni networking and job placement assistance. 

If you are looking to gain data science skills quickly, you may want to pursue a data science certificate. In addition, online data science boot camps can last several months, compared to the four-year degree path. If you already have a degree in another field, a boot camp could give you the technical know-how to transition to a data science role. Otherwise, the boot camps focus on the technical side and may not prepare you for a managerial or leadership role.

You can earn a master’s degree in data science via online courses or on campus in as little as a year. A master’s degree can prepare you for leadership positions as well as refine your data skill set. With a bachelor’s degree, you may be responsible for data cleaning and analysis, handing your work up the chain to others. A master’s degree can prepare a data scientist to lead or participate in interdisciplinary teams, looking for answers that are fundamental to the organization’s success. 

A Ph.D. in Data Science is a degree designed for research. You may conduct original inquiries in your field of interest, such as machine learning or big data. You’ll apply existing theories to the research, and may develop your own in the process. Keep in mind a Ph.D. program requires extensive individual study and research. You may not spend much time in group activities or collaborating with industry partners. However, you could become a recognized expert in your field, working with the latest technology. You may qualify for leadership or executive positions or a post as a professor. Because Ph.D. program requirements vary from coursework to research, the length of time to obtain a doctorate varies.

A Ph.D. student may be asked to make a unique contribution to research in the field. You’ll spend two to three years researching and writing a dissertation and preparing to defend it. In the meantime, you may also teach undergraduate classes.

The skills a data scientist uses will depend on their functions within an organization. Some companies see them as data analysts, spending a lot of time cleaning and sorting data and transforming it into useful formats. They may conduct exploratory data analysis to identify missing data and develop a plan to address it in a subsequent report. Other jobs may tend toward data engineers that develop reservoirs for data collection. As your career develops, you can pursue specialized education and experience to take on new responsibilities. 

If you are curious about the world around you, have strong organizational and communication skills, and are able to solve problems despite frustrations, becoming a data scientist might be a good fit for you.

Computer and information research scientists, which includes data scientists, are in high demand, as job demand is expected to grow 16% from 2018 to 2028, much faster than average, according to the Bureau of Labor Statistics (BLS). Median pay in 2019 was $122,840 per year for those with a master’s degree. Salaries are highest in California and around the Washington, D.C., region in Virginia.

When it comes to careers, there are plenty of reasons to become a data scientist. A data analyst is a typical entry-level job title for a position that uses data to answer business questions. A data scientist works at a higher level, using machine learning models to develop predictive or prescriptive data models. This level may require programming skills as well as a solid understanding of the business. Other positions include a business intelligence analyst, data warehouse architect, systems or operations analyst, and machine learning engineer.

Each of these positions may need specialized knowledge and on-the-job training to deliver results to an organization. The salary will vary by job title and organization, but there are currently multiple projected opportunities for those with data science expertise.

Last Updated July 2020