Career Outlook for Data Scientists
Data scientist is a job category that barely existed a decade ago. But today, in an era of big data, with the use of data surging and dependence on computer databases growing, these workers play increasingly important roles. The role of a data scientist can be found in a wide range of disciplines, under a variety of different titles, such as a data engineer, data analyst, machine learning specialist and program analytics engineer.
Types of Data Science Jobs
Data scientists work with computers to interpret and extract meaning from reams of complex information. A data scientist is, in many ways, a data miner — someone capable of finding answers in a sea of information. And those answers are often found by writing computer algorithms that can find meaning or insights in all that information. But first, the data scientist often needs to “clean” the data, which is sorting through information coming from different sources (other databases, surveys, test scores, almost anything that can be counted) and often in different formats. Merging these sources of information cohesively is essential.
It is then the data scientist’s job to organize the data and make it useful. That often requires number-crunching skills as well as the ability to use software tools. A data scientist needs to understand how to use statistical programming languages such as Python and have the ability to translate requests for data into workable computer queries. A typical day in the life of a data scientist starts with examining a database and working with other departments to determine what they want to learn from the information. The data scientist probes for answers and helps analyze the information for valuable insights.
Demand for data scientists — also known as computer research scientists — is strong, according to the Bureau of Labor Statistics. The number of data scientist jobs is expected to grow 22 percent over the next decade — much faster than the average growth rate for all jobs.
“There will be a shortage of talent necessary for organizations to take advantage of big data,” noted a report by McKinsey consultants. The Harvard Business Review called data scientist “the sexiest job of the 21st century” and IBM predicts demand for data scientists will jump 28 percent by 2020.
A master’s degree in data science or a related field is often required to become a data scientist.
The job of data scientists is still relatively new. So the career path for a data scientist is still evolving. The positions differ within industries. But just about every industry today has the need for someone to make sense of all the data that are collected. Some companies hire their own data science teams. Others use data scientist consultants.
Data Scientist Salaries in the United States
The median salary for data scientists is $126,830 a year, according to the Bureau of Labor Statistics. It’s important to note that salaries vary by geography, local cost of living and career path. For example, the highest median salary for data scientists working for software publishers is $132,190, while the lowest median salary for data scientists working for colleges and schools is $77,240.
Data scientist jobs tend to be clustered in states with a big tech presence, such as California, Maryland, Virginia, Texas and Washington state. But there is also a high concentration of these jobs in states such as Utah, Rhode Island and New Mexico.
The U.S. federal government is one top employer of data scientists, according to the Bureau of Labor Statistics, including some of the 70 who work in the Las Cruces, New Mexico, which is home to the White Sands Test Facility and White Sands Missile Range.
The most data scientist jobs are in the Washington, D.C., area, with more than 2,600 data scientist positions, and the mean annual salary there is $130,970. Another 1,700 workers are in the Maryland suburbs just outside Washington stretching up to Baltimore. The mean salary there is slightly lower, from $108,820 to $114,110.
On the West Coast, Silicon Valley employs many data scientists, along with Seattle, home to tech firms such as Microsoft and Amazon. These areas also boast among the highest mean salaries — from $129,600 to $144,530.
But data scientist jobs can be just about anywhere in the United States. The Bureau of Labor Statistics reported data scientists working in the Huntsville, Alabama, region earn an average salary of $144,580. And 50 data scientists work in the Melbourne, Florida, area.
Data Scientist Salaries by State
|State*||Annual median wage (2017)|
District of Columbia
* Information not available for all states
Data Scientist Jobs
Data scientist jobs are not just found in tech companies. Different types of data scientists are employed by firms in a variety of sectors. As the need for big data insights grows, so does the demand for people able to sift through these mountains of information. Retailers can use data scientists to plow through information collected about which products are selling. Target has acquired several companies that specialize in big data — including one that went from studying hypersonic aeronautics fields for the government to studying Target’s retail guest services. Other retailers need data scientists to run the recommendation engines on their websites, the boxes that make suggestions based on a visitor’s buying and search history. Even prices are set, in part, by insights from data scientists. A study by McKinsey highlighted the need for data science insights by estimating that 30 percent of the thousands of pricing decisions made by companies fail to deliver the optimal price — the one that generates the most sales at the highest price point. Data scientists can help with that.
Automakers have data scientists to learn about customer preferences and to help develop driverless vehicles. Data scientists at Ford Motors Co. help identify more efficient ways of manufacturing cars and trucks.
Wall Street traders hire data scientists to see patterns in the flood of financial data that pours out every day. Research institutions, including medical centers, use data scientists to scour medical results. The Fred Hutchinson Cancer Research Center in Seattle helped lead a study that used complex data analyses to study cancer. IBM’s Watson Health and other big data companies use data from electronic health records to uncover potential new interventions and cost-saving opportunities.
Sports is another big growth area, as analytics are used to find some hidden advantage on the playing field. The English soccer club Arsenal hired a data scientist from the maker of the Candy Crush video game franchise so the soccer club could learn how to use data to improve training and performance of its players. In baseball, the Houston Astros have invested heavily in making data-driven decisions about players and strategy, which was credited with helping the team win the 2017 World Series.
Data Scientist Career Path
If you’re interested in an online master’s in data science or a career in data science, it’s important to know what employers expect when they consider levels of education and experience among candidates. A master’s degree is often required for most data science positions, and being a data scientist requires a solid understanding of computers and software programming, as well as strong problem-solving and critical-thinking skills.
Data scientist skills are largely technical, such as creating and managing databases. But data scientists often work with other departments, such as marketing or research, responding to their requests for information, so having strong interpersonal skills helps. And because data scientists work in a variety of fields, it can help to have college classes or work experience in a particular industry. If you plan to become a data scientist at a hospital or medical research institution, experience with biology or chemistry might be required.
There are no licensing requirements to become a data scientist. After you graduate from an accredited master’s program in data science, you may qualify for a range of different jobs — it is important to identify which companies and areas of interest are the best fit.
Citation for this content: DataScience@SMU’s online master’s in data science program
Last updated March 2019