Though it’s possible to become an entry-level Junior Data Scientist with a bachelor's degree, or to learn data science skills through "DIY" free courses and trainings, according to a 2022 survey, as many as 93 percent of Data Science/Analytics and AI professionals hold either a master's or PhD degree. And using job postings analytics, Indeed.com recently found that about 45% of Data Scientist job postings over the past 3 years required at least a master's or doctoral degree.
According to leading Data Science recruiting firm Burtchworks, early 2022 has been incredibly competitive for data science & analytics hiring. In addition to getting an edge during the job application and interview process, pursuing a high-quality, accredited Master of Data Science degree is worth it if data is transforming your industry, you want to transition careers, you’re looking to boost your salary, or you simply just love gaining knowledge.
Here are four situations where it is worth considering a graduate data science program:
1. Data is Transforming Your Industry and Profession
2. You Want to Change or Transition Careers
3. You Want to Increase Your Salary
4. You Love Gaining More Knowledge
Situation 1: Data is Transforming Your Industry and Profession
Maybe you're thinking, How can I stay several steps ahead in my profession?
While data-enabled digital transformation will eventually force every industry and organization to evolve (or revolutionize) their business models, processes, capabilities, and skills, some sectors and companies are further along than others. Depending on the level of data and tech maturity in your workplace or within your current occupation, you may already be considering how to upskill and reskill in data science, machine learning/AI, or business analytics to remain relevant, in which case, a master’s degree in data science would be worthwhile.
Let's consider 3 "before and after" examples to illustrate this digital and data transformation:
- From GIS to Geospatial Data Science. GIS, which stands for geographic information systems, are computer systems that Geoscientists, Engineers and Architects use to collect, manage, and visualize (or map) spatial data. Traditionally, a GIS enables data analysis across everything from natural disaster management and urban planning, to soil and seismic analysis and drilling optimization. In the era of big data, a GIS and its data can be integrated into a machine learning model, effectively acting as code (or one input) within a broader data science program. Data scientists and Machine Learning engineers who can architect these scalable, repeatable data processes will be highly coveted in the emerging workforce.
- Big Data = Better Access to Clean Water. Historically, a Water Quality Specialist or Environmental Technician was often responsible for manually taking water samples in the field, testing the water, reviewing statistical data, and monitoring programs on an ongoing basis. Now, with the advent of low-cost and low-tech sensors, teams of Engineers can easily deploy distributed solutions controlled by sophisticated, cloud-based computer systems to measure if water is clean or contaminated, with little to no manual intervention by human technicians.
The resulting "big data" requires new data science skills to capture, clean, model, structure, analyze and visualize vast amounts of collected data, allowing highly informed and effective decisions about how and where limited resources should be spent to improve sanitation and safety for humans, animals and the environment. - The Promise of Personalized, Holistic Healthcare. When a person gets a disease, is treated, and ultimately cured, we consider the illness "resolved" and quickly return to the daily demands of modern life. Oftentimes, this is a limited and reductive view of an individual's overall health, with many of the essential factors of a patient's life (like work stress and over-the-counter medicines) invisible to those medical professionals administering care. As a patient goes about her life every day, with the proper privacy disclosures, data could be harnessed to provide better, more personalized treatments, technologies and approaches for everyone.
Keep in mind, data science will complement your existing domain of expertise--not replace it. The skills of data science, like Python programming, will expand and sharpen the "tools in your toolbox," and the applications are vast. If you're considering a master's in Data Science, look for accredited, reputable university programs with employer relationships and opportunities for real-world industry projects specific to your intended application, like Energy, Engineering, or Medicine.
Situation 2: You Want to Change or Transition Careers
Data scientists usually fall into two camps – those who know math really well but don’t code efficiently, and those who are great coders but don’t have a solid foundation in statistics. I can speak to both sides, so I am right in the middle – exactly where I wanted to be.
- David Sullivan, MCS Alumni, Data Scientist at New Knowledge. Read more about David’s data scientist career.
Demand for Data Scientists is expected to grow by as much as 36% or more over the next 10 years—much faster than the average job growth of 8% across other industries. That means pursuing a Master of Data Science degree, particularly a program that features experiential learning on real-world data science projects, is one of the best ways to switch careers into a high-demand, growing occupation.
In terms of which occupations people are switching from, at Rice, we see many Computer Science majors who pursue Data Science master's degrees, but Statistics, Math, Engineering, Economics, Journalism, Sports and Analysis-related majors (for example, Public Policy analysis) are also very common.
As mentioned previously, Indeed.com found that about 45% of Data Scientist job postings required a Master's or Doctoral Degree. This is partially because of the advanced math, statistics and computer science skills required, particularly among Senior or Lead Data Scientists. So, if you’re looking to change careers, obtaining a master of data science degree will be worthwhile when making the transition.
Situation 3: You Want to Increase Your Salary
As explained above, it’s possible to become a Data Scientist with a bachelor’s degree, but those who enter the field with only an undergraduate background might earn an average salary of about $67,000 per year, depending on the industry and city. With a Master of Data Science degree and more hands-on data science experience, that annual salary can increase to about $98,000-130,000 or more. Because of high demand and low supply of candidates with the right technical skills, it’s also common for employers to offer $10,000 more to applicants with a Master of Data Science degree, even if they’re applying to entry-level positions.
Earnings by Data Science & Analytics Job Titles
The table below shows how much you can expect to earn in general data science and analytics positions with a master’s degree:
| JOB TITLE | JOB DESCRIPTION | MEDIAN SALARY* | JOB OUTLOOK* |
|---|---|---|---|
| Data Scientist | Data scientists develop statistical models to explore and analyze data at scale (using computer science & programming tools) for use in real-world applications. | $98,860 - $138,007+ | Demand is expected to increase as much as 36% between 2021-2031. |
| Data Science Manager | Data science managers identify opportunities to use data science within an organization and deploy teams of data scientists to realize business value. | $162,000 | Demand is expected to increase as much as 36% between 2021-2031. |
| Business Analytics Manager | Business analytics managers capture and use data to improve operational efficiencies across functions like operations and supply chain or to drive growth within strategy, marketing and/or sales. | $149,167 | Demand is expected to increase as much as 21% between 2021-2031. |
| Business Intelligence Manager | Business intelligence managers acquire data to make an organization more "intelligent" (i.e., to provide a competitive advantage), reporting and communicating data to influence overall effectiveness. | $131,490 | Demand is expected to increase as much as 11% from 2021-2031. |
| Quantitative Analyst | Quantitative analysts ("Quants") use quantitative methods (i.e. advanced math models, algorithms) to improve financial performance or risk management, identifying trends and anomalies or to make predictions about future performance. | $98.527 | Demand is expected to increase as much as 9% between 2021-2031. |
| Cloud Analytics Consultant | Cloud analytics consultants use a company’s cloud computing applications and technology to store and process sensitive big data. | $102,600 | Demand is expected to increase as much as 35% between 2021-2031. |
| Financial Analyst | Financial analysts engage in research and data analysis to support the effective financial management and investments, risk management, growth and profitability of an organization. | $95,570 | Demand is expected to increase as much as 9% between 2021-2031. |
| Machine Learning Engineer | Machine learning engineers design self-learning software using algorithms. This software is then meant to make predictions and continuously learn and adapt. | $129,739 | Demand is expected to increase as much as 40% by 2024. |
| Data Architect | Data architects develop interconnected systems to store, manage, process, and secure sensitive data. | $101,000 | Demand is expected to increase as much as 9% between 2021-2031. |
| Data Engineer | Data engineers design the infrastructure required to store and protect data across relational databases and cloud storage services like AWS or Azure. | $92,503 | Demand is expected to increase as much as 8% between 2021-2031. |
| Database Administrator | Database administrators manage relational databases, including the acquisition, end-to-end management, and governance and security of sensitive data assets. | $101,000 | Demand is expected to increase as much as 9% between 2021-2031. |
| Chief Data Officer | CDOs oversee an organization's strategic use of data and analytics, helping to ensure a company acquires the right data, unlocks the financial value of its data assets, and complies with evolving privacy regulation. | $178,240 | Demand is expected to increase as much as 8% between 2021-2031. |
| *Source: U.S. Bureau of Labor Statistics, Indeed, Salary.com, Forbes | |||
Situation 4: You Love Gaining More Knowledge
Many of Rice's Master of Data Science students are passionate about the pursuit of knowledge, constant learners at heart. For many, completing graduate school is seen as a major life event and personal goal alongside graduating from college, buying a house, and having a family.
Those who value gaining knowledge care deeply about how they learn. We find that many students are less interested in MooCs (massive open online courses) where they may be "faceless" among hundreds or thousands of students and, instead, look for a more immersive and interactive experience. They also seek out small, intimate cohorts of likeminded, curious, continuous learners.
Some students benefit greatly from the structure, networking and motivation of a formal master's program, including the social interaction with their student peers, 1:1 interaction with world-class Faculty who are working on groundbreaking research, and introductions to industry partners looking to hire data scientists.
As is true of many reputable universities, Rice's world-class faculty care about their students, developing close 1:1 relationships and transforming lives through knowledge, discussion and debate. While the coursework is challenging, when students emerge with their master's degrees in data science, they feel an enormous sense of pride and confidence in their command of the material. Our students also feel part of a close-knit community of alumni, drawing on these relationships for decades after graduating.
Deciding if a Master’s in Data Science is Worth it for You
How can you tell if a degree in data science would be worth it for you? Think about the things you most enjoy doing at work, as well as your personal values. If you like finding answers, seeking truth, conducting analysis, and using data to make or recommend better business, governmental or societal decisions, a master’s degree in data science could be worthwhile. If you already have the following knowledge and technical skills, you could be a candidate for the online MDS@Rice program:
- Strong math and statistics skills, specifically: High-school level algebra and trigonometry, College-level calculus, basic discrete math skills, and boolean logic
- Ability to write basic programs in a coding language like Python, R or SQL
Enrolling in a robust, online program like the MDS@Rice will give you exposure to different areas of data science--from advanced business analytics with Python to machine learning models. It will also enable you to pursue a degree part-time on a flexible schedule, while continuing to work if you choose. You’ll be able to learn at your own pace, attend live sessions to engage with faculty and peers, and network with leading employers to find a new role that interests and excites you.
What is the Value of the Rice Online Master of Data Science Program?
Pursuing any higher education degree requires an investment of both time and money, and that is understandably a top consideration for many students. However, for students who will garner higher salaries upon graduation and pay back their tuition within a few years, there's no better return on investment than feeling prepared for fast-evolving workplace demands.
The MDS@Rice program allows you to pursue an advanced degree on your own time while still giving you access to industry experts, supportive faculty members, and a robust curriculum that will prepare you for real-world situations. With a best-in-class online learning platform and ability to specialize in machine learning or business analytics, you’ll get the same quality education you’d receive in person without having to stick to a strict schedule that interferes with work and other obligations.
To graduate, students complete a capstone project where they will encounter real-world data science problems and create solutions that solve actual pain points for businesses, government and non-profits. This project strengthens your resume and can help your application by verifying your skills and giving employers something concrete to base their decisions on, increasing the amount of trust future employers are willing to put in your abilities from day one.
Learn More About Our Master of Data Science Curriculum
The Master of Data Science at Rice University is a great way to enhance your skills and set yourself up for a successful and in-demand career. Learn more about our curriculum to see if the program is a great fit for your goals and apply online today.