Data science is one of the fastest-growing occupations, according to the Bureau of Labor Statistics (BLS), which predicts a 36 percent growth in employment in this role between now and 2031. This pace of growth outstrips other top jobs, including web developers and physician assistants. The BLS isn’t alone in forecasting significant expansion in data science. The World Economic Forum expects the field to attract workers from other occupations as those decline and data-related fields mushroom. LinkedIn also recognizes the industry’s potential, placing machine learning engineer, a data science-related position, on their list of the fastest-growing jobs last year.
In fact, growth is so promising that the field might be developing too quickly for companies to keep pace with hiring data scientists. In a survey of hiring managers, Upwork reports that data scientist is one of the most challenging roles to recruit. Anaconda’s 2022 State of Data Science report echoes this finding, with 63 percent of respondents saying their organization is at least moderately worried about the field’s talent shortage. In its survey of information technology leaders, Velocity found that big data skills represented the second most significant shortage in tech.
Hiring managers’ challenges may be prospective data scientists’ boon. The demand for professionals with advanced data handling and analytics skills is reflected in their pay—experienced U.S.-based data scientists earn median salaries of around $150,000. According to Karen Panetta, dean of graduate education at Tufts University School of Engineering, Tufts’ 2022 data science graduates received offers as high as $135,000 before even graduating.
In addition to six-figure salaries, data science offers some of the most satisfying jobs available. Data-related positions, including data scientist, data engineer, and machine learning engineer, are in the top 10 of Glassdoor’s list of the best jobs in 2022, each ranking highly for overall satisfaction. Prospective data scientists can embark on this promising career path by enrolling in Tufts’ online Master of Science in Data Science (MSDS) program, where they learn the skills necessary to succeed in the industry and fill the data science talent shortage.
Why the Data Science Talent Shortage Persists
The data science talent shortage might seem like a paradox. Why is it difficult to find applicants for some of the highest-paying and most satisfying jobs? The answer is the advanced skill set required to qualify for most data science jobs.
To understand why the talent shortage persists, it’s essential to set data science apart from more routine data analysis. Though still in high demand, data analysts deal primarily with structured data—data sets that fit neatly into spreadsheets. However, more and more new data is either unstructured or semi-structured. This includes things such as tweets, videos, and images. This data doesn’t fit on spreadsheets but can offer valuable insights for organizations with the tools to analyze it, such as advanced software engineering, data modeling, and cutting-edge artificial intelligence and machine learning technologies. Data scientists need advanced training to develop these skills, and firms have trouble finding professionals with the necessary education to fill data science positions.
How Universities Help Supply Catch Up with Demand
According to Kaggle, advanced degrees are the norm in data science and held by around 64 percent of professionals in the field. So, it follows that solutions to the data science talent shortage are found at universities as they prepare prospective data science professionals to succeed in this industry.
Universities Help People Transition into Data Science Careers
In recent years, data science was primarily populated by PhDs in math or computer science—academics skilled in statistics and machine learning who could break down complex data sets. However, demand for data scientists has spawned new degree programs that teach all the relevant skills to aspiring scientists with no background in the field. These programs inject fresh talent into the industry, alleviating some of the skill shortage, but they are responding to student demand, as well. According to Dean Panetta, “Students want to hit the market and say, ‘I have the depth to jump into this field and be an immediate technical contributor.'” Programs such as Tufts’ online MSDS deliver that outcome, producing job-ready graduates for this talent-needy field.
Universities Update the MSDS Curriculum to Keep Pace with Technological Change
As a technology-dependent field, data science evolves quickly to keep pace with innovations. For instance, earlier in the field’s history, data scientists with advanced degrees could spend significant amounts of time cleaning data on so-called data janitor work—cleaning data sets in a repetitive process to make them digestible for data-analyzing machines. As one Twitter user wryly notes, data sets are rarely clean—survey respondents might say they live in “St. Albans,” “St Albans,” S.Albans,” or any number of phrases meaning the same thing. Human analysts recognize that these are all the same place, but machines cannot make these kinds of distinctions as easily.
Advances in machine learning and natural language processing will relieve data scientists of some data preparation duties. Such automation will allow them to use their advanced knowledge on more sophisticated projects rather than repetitive data janitor work. And this is only one way that data science is evolving. Other emerging technologies include faster computers, new data analysis methods, and more AI solutions, including computer vision. The best MSDS programs constantly update their data science curriculum to stay current with developments in the industry and prepare students for the work they will perform after graduation.
Universities Help Ambitious Professionals Meet Employer Expectations
Prospective data scientists may find themselves at a crossroads. Many education programs claim to equip people with machine learning and data analysis skills. However, bootcamps often fail to live up to this promise, spending too little time on more complicated material to produce critical thinkers ready to become data scientists. Data science is a complex subject, and successful data scientists need a diverse and deep skill set beyond what they can learn in a few weeks at a bootcamp.
Many contemporary data science job postings at top firms, including Amazon and Google, prefer or require their candidates to hold master’s degrees. MSDS programs respond to this need, producing graduates ready to meet employers’ expectations.
A data science master’s degree offers two advantages for professionals applying to data science jobs. First, it equips the holder with the relevant and necessary skills for data science work. Second, it signals to human resources professionals, who are not data scientists, that the candidate is fully qualified for any data-related position. This helps MSDS graduates pass the initial stages of the job application process, putting them in front of interviewers who “speak” data science and fully grasp the value of their backgrounds and skills.
Why Tufts University’s Data Science Master’s Program Is an Excellent Training Ground
Demand for data scientists with credentials from top-tier institutions makes this an ideal time to pursue an online MS in Data Science at Tufts University. Tufts teaches emerging technologies in a curriculum that adapts to technological innovation. Students learn skills in machine learning, artificial intelligence, and big data relevant to the current demand in the industry. Most importantly, they put these skills to work on real-world data science projects in a capstone course, completing work they can present to prospective employers as proof of their expertise.
Tufts MSDS graduates excel in the job market thanks to the skills they acquire and the credentials they earn. Student support resources such as Tufts’ career center connect students with high-profile tech employers and promising startups in the Boston area and worldwide. The program doesn’t just train students in all the skills necessary to work in data science—it prepares them for professional success in the industry.