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First, some facts. Of the Data Science graduates we've analyzed , here's how many have used (or NOT used) their degree in their career:
These are estimates based on AI analysis of 77 LinkedIn profiles (see below).
The verdict? Significantly above average. Overall, with an average relevance score of 78%, Data Science graduates have a much higher likelihood (+11%) of finding work in this field compared to the average graduate across all fields:
And for comparison, here's the chart for all profiles we've looked at across all degrees.
Also, after graduating, only 22% of these graduates have pursued further education other than another Bachelor's degree (such as a Masters degree or other), compared to the average across all profiles of 35%. This suggests a Bachelors degree is enough for most Data Science graduates, and it's normal to look for work straight after graduation.
See the details:
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Relevance score: 100% We think this person has gone into a career highly relevant to their degree.
DEGREE INFOGraduated in 2020 from University of Rhode Island with a Bachelor's degree in Data Science. Also pursued further education since (see below). JOB HISTORY SINCE GRADUATIONGraduate Research Assistant (Health Outcomes) University of Rhode Island May 2021 - Dec 2021 Statistician II Karna, LLC Nov 2021 - Oct 2022 Scientific Data Analyst(vaccine breakthrough) Apex Systems Oct 2022 - Present FURTHER DEGREES DONE SINCE GRADUATINGMaster of Science - MSUniversity of Rhode Island 2020 - 2021 ABOUT10+ years working experience in the Manufacturing industry, and 4+ years working experience in the finance industry. Experience in business problem solving and insight delivery with statistical know-how, programming skills (R, SAS, Python, SQL). Certified Project Management Professional, familiar with agile frameworks, with reporting, budgeting, and forecasting experience. Experience with predictive modeling and Machine Learning including supervised and unsupervised learning, experimental design, execution, and measurement. Experience in a strategic and financial role that focuses on interactive manipulation and analysis of large datasets in SQL. Experience with cross-functional stakeholder influence and navigating ambiguity. Understand the ICD9/10 code, Medicaid, and Pharmacy Claims Data. |
The top 10 most common jobs done by the graduates we've analyzed (ranked most common to least) are:
The journey of Data Science graduates reveals a fascinating trend in the types of jobs they procure after completing their degrees. Across various educational institutions and graduating years, many of these individuals have found themselves in roles such as Business Analysts, Data Scientists, Software Engineers, and other positions that either employ or indirectly utilize the skills acquired during their studies. From the analysis provided, it becomes apparent that there are several common roles among these graduates, with a strong focus on jobs requiring data analysis, statistical skills, and technical expertise in programming and data management.
A notable number of graduates have taken up positions as Business Analysts or Data Scientists. These roles directly align with the curriculum of a Data Science degree, which emphasizes statistical analysis, data interpretation, and problem-solving. For instance, many Business Analysts leverage their data skills to analyze trends, provide insights, and support decision-making processes within their organizations. Similarly, Data Scientist roles require a heavier emphasis on algorithmic programming and statistical modeling, which are crucial components of Data Science education. Conversely, some graduates have ventured into roles like HR Analysts or Credit Analysts, where the relevance to Data Science is less pronounced, indicating a variety of career paths even outside the traditional realms of data-focused jobs. While these positions may ask for analytical skills, they often do not require the rigorous technical knowledge and methodologies typical of Data Science degrees.
In summary, a significant portion of Data Science graduates finds jobs that are either directly relevant to their field or tangentially related; however, the immediate fit varies greatly among individuals. Many end up in roles that effectively harness their training, like Business Analysts and Data Scientists, while others may take on positions that are less aligned with their education. This variance raises the question of market alignment, skill application, and the diverse pathways available for Data Science graduates as they step into the job market.
Here is a visual representation of the most common words in job titles for Data Science graduates:
So, looking at the career paths of these data science graduates from various universities, it seems like there are some solid trends that pop up. Fresh graduates usually land themselves in analyst roles or software engineering positions related to data, which makes sense given the skills they acquire in their degrees. For example, many from Bryant University and University of California, Berkeley jumped straight into business analyst roles or software engineering. This orientation towards entry-level jobs that pertain to data-related tasks is pretty common across the board.
Fast forward about five years or so, and the picture starts to differ a bit based on how aggressive they've been in climbing the career ladder or shifting roles. Some people, like those from Northrop Grumman and Liberty Mutual, seem to have moved up fairly quickly into more senior roles, still sticking to the data science and technology arena. That said, there are also a few folks who have awkwardly veered off into unrelated territory or lower-level jobs, like working as a project worker or support technician. This suggests that while some graduates are making amazing strides in data-centric careers, others may be struggling to stay aligned with their field or earning potential.
Overall, I'd say that graduates who pursued careers in data science generally start strong, often landing roles that are on track with their education. But as they move on, the success in climbing the corporate ladder or transitioning into more specialized roles can vary widely. Some stick to high-level jobs with notable companies, while others may find themselves in positions that don’t fully utilize their skills or knowledge gained from their degrees. If you're considering a career in this field, it looks like getting a data science degree can be a great launch pad, but you’ll definitely want to be proactive about your career choices to stay aligned with your goals.
A Bachelor’s degree in Data Science can be a bit of a mixed bag when it comes to difficulty. If you’re into math and programming, you might find the coursework manageable—it's definitely challenging, but it’s not impossibly hard. However, if you're not super comfortable with statistics or coding, you might struggle a bit more than average. Overall, it does require a solid amount of dedication and effort, but it’s not the worst degree out there. Just be ready to put in the work, especially during those intense project deadlines!
Most commonly, in the LinkedIn profiles we've looked at, it takes people 4 years to finish a Bachelor degree in Data Science.
Looking at these Data Science graduates, it seems like a lot of them are finding solid job opportunities pretty quickly after graduation. Many of them have landed roles that not only seem stable but likely pay well, especially those working with big tech companies or in high-demand areas like AI and data analytics. For instance, graduates from well-known universities like UC Berkeley and University of Michigan have secured positions at reputable firms where salaries can be quite competitive. However, some may not have that same level of earning potential, particularly if they are starting in roles like interns or entry-level positions. But overall, it appears many are on a promising career trajectory, with room to grow and earn even more.
It’s clear that their chosen fields are generally lucrative, especially as they gain experience. With roles like Data Scientists, AI Engineers, and Software Engineers often bringing in six-figure salaries, it stands to reason they can really ramp up their earnings fairly quickly. Even graduates who are currently in lower-level roles have the potential to increase their income significantly within a few years as they gain more experience and skills. So, yeah, it looks like most of these folks are setting themselves up for some decent money in the long run, which is pretty awesome!
Here is a visual representation of the most common words seen in the "about" section of LinkedIn profiles who have a Bachelor degree in Data Science. This may or may not be useful:
