University of Wisconsin Data Science Degree

Women in Data Science: Meet Jennifer Cox, UW Data Science’s Program Manager

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As part of our Women in Data Science series highlighting the importance of women in the data science industry, we’re shining the spotlight on Jennifer Cox, a M.S. graduate in data science and the program manager for the 100 percent online University of Wisconsin Master of Science in Data Science program.

After graduating from UW-Platteville in 2005 with a bachelor’s degree in psychology and a minor in business, Jennifer worked as a program manager at a group home for adjudicated youth. However, she missed using the technical skills she gained in her psychology degree, specifically the statistical components.

program manager Jen Cox with her three daughters
Jen and her three daughters

Jennifer then transitioned to working in a research project management role within the School of Medicine and Public Health at UW-Madison, which is where she discovered the data science field. She was exposed to how databases, programming, and statistics merge together to investigate issues in healthcare. Jennifer also learned how big data, artificial intelligence, and machine learning are used to advance knowledge of disease, and offer opportunities for better prevention and treatment.

While in her role at the UW School of Medicine and Public Health, Jennifer decided to pursue a master’s degree in data science. She had been researching programs since graduating with her bachelor’s degree, but nothing seemed like the right fit. Then, she found the online UW Master of Science in Data Science program. She began her degree in 2016 while working full-time and raising her young children.

“It was not easy, but with support and encouragement from my family and the Data Science program staff, I was able to graduate in 2018,” Jennifer said. “I was thrilled to have completed another major goal in my life and in something I felt so passionate about.” 

The UW Data Science program helped Jennifer gain confidence in her ability to do her work, and her employer noticed this. After she earned her degree, Jennifer joined a team of clinical informatics professionals to create a master’s degree program. 

“I learned a lot about academic program development and found I enjoyed putting together the many different components required to effectively run a program,” Jennifer said.

Jennifer began her role as program manager for UW Master of Science in Data Science and UW Bachelor of Science in Applied Computing in August of 2020. 

The following Q&A with Jennifer Cox spotlights her role as program manager and as a woman in the data science field.

Jen and her family upon graduation with her master’s degree in data science in 2018

What is your role as a UW Extended Campus program manager?

As a program manager of the MS in Data Science and BS in Applied Computing, I serve as a liaison to the programs’ partner campuses to establish systems, policies, procedures, and business practices that support effective operations. I see myself as a cheerleader for the programs, encouraging and supporting our partners to communicate and make decisions together as a team to best support our students. If we have shared goals, and an understanding of one another, we can best serve our students. I also collaborate with and provide support to internal UW Extended Campus team members to satisfy goals of these programs.

It is important to me that the programs are successful because I’m very passionate about both of these fields. I believe these programs are very strong and UW Extended Campus does a great job of setting students up for success. Graduates of these programs are the future of these fields, so I want to set them up to be the best they can be.

Why did you choose the UW Data Science program as a student? What unique perspectives do you bring to your role as Program Manager?

As a Wisconsin native, I knew I could trust the quality of UW programs. I chose the UW Data Science program because I liked that it was 100 percent online and that I could alter my school schedule based on my personal needs. I also felt the curriculum fully covered the skills needed to be successful in the field, with a good mix of technical and nontechnical coursework. The program also leverages instructors from several UW campuses. These instructors are experts in their domains and they work hard to ensure course content is continuously updated to keep us relevant in the field.

[perfectpullquote align=”full” bordertop=”false” cite=”” link=”” color=”” class=”” size=””]”Graduates of these programs are the future of these fields, so I want to set them up to be the best they can be.” – Jennifer Cox, UW Data Science Program Manager[/perfectpullquote]

I am utilizing the skills I obtained as a UW Data Science student in my program manager role by using data to understand organizational needs and to guide program decisions. I’m also able to effectively communicate data-related information to all audiences so both technical and nontechnical team members can understand. I also have the advantage of experiencing the program firsthand as a student, so I am able to share a student perspective with our campus partners.

Why are women crucial to the data science field?

Women bring unique perspectives and experiences to all areas of work. Leveraging women’s views allows a more complete understanding of an issue and how resolution might be reached. Gathering diverse perspectives, in general, will likely lead to an outcome that is more applicable to the masses. 

Women should pursue a data science career if they have an interest, and they shouldn’t feel discouraged by the predominantly male field. There is an increasing amount of women working in technical fields and rightfully so. We need highly skilled women to use their experiences and perspectives to bring understanding to all areas of data science.

Women and men currently in the field can support women entering the data science field by encouraging involvement and providing mentorship. Women should believe in themselves and have confidence that they are a valued contributor to the field.

Jen and her family before her youngest was born

What advice do you have for prospective data science students?

Getting a master’s degree is both a financial and time commitment. You should be honest with yourself about what your interests are and what you want to get out of completing the degree. It’s also important to make sure the outcomes of the program align with your goals and that the degree makes financial sense.

Having a support system is also really important. You should discuss your coursework schedule and how long it might take you to earn the degree with your support system. It’s likely you will have to give up some time with your family and friends to be successful, but understand it’s only temporary and it will pay off in the end.

How will data science impact the future?

In this digital age, data surrounds us and, when used and interpreted appropriately, we can improve the world around us. Organizations can use data science to improve business practices, such as making operations more efficient or improving products and services. For example, healthcare organizations can use data to improve knowledge of diseases and how to best prevent and treat them. Information gained from harnessing data can allow us to learn things that might not have been possible before.

UW Data Science strives to be inclusive

In an effort to highlight the importance of women in the data science industry, this is the second post of a blog post series from UW Data Science. The Women in Data Science series features the crucial roles women take on within the computing field. Additionally, the series highlights students, faculty, and program leaders of the UW Master of Science in Data Science program who share their experiences as women in the data science industry, and offer advice for breaking into the male-dominated profession. 

The UW Master of Science in Data Science program aims to create an inclusive environment for all. If you’d like to learn about graduates of the program, read about Venmathi Shanmugam, a modeling and simulations engineer working at the Veterans Affairs office, and Halee Mason, a lead data scientist at Cloud9 Esports, Inc. You can also learn about our diverse faculty members.

Have questions about the courses, tuition, or how to apply? Talk with an enrollment adviser by emailing learn@uwex.wisconsin.edu or calling 608-800-6762.

Women in Data Science: Why They’re Critical to the Data Science Workforce

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According to a 2020 National Center for Women and Information Technology (NCWIT) report, women make up 57 percent of the overall workforce, but only 26 percent of computing and math occupations. This is the first post in a new series from the University of Wisconsin Master of Science in Data Science to highlight the importance and need for women in the data science industry. The Women in Data Science series will feature the crucial roles women take on within the computing field. Additionally, the series will highlight students, faculty, and program leaders of the UW Master of Science in Data Science program who share their experiences as women in the data science industry, and offer advice for breaking into the male-dominated profession. 

Though there is a lot of work yet to be done for women’s inclusivity in data science, there are a few statistics that are worth celebrating. In this first blog post, we take a look at hiring trends, strengths women bring to data science roles, and how women can stay competitive in the industry.

Positive job growth for women in data science

First, let’s break down the percentage of women in computing occupations. A 2022 Burtch Works study found that the number of women in data scientist roles has reached 24 percent, an increase from 2018 where just 15 percent of data scientists were women. The same study also found that the largest percentage of women in data science roles are in the entry-level individual contributor category.

These numbers indicate a possible increased presence of women in the field, along with the beginning of women-led leadership. However, there is still a great need for growth in the computing field for women and other minority groups, especially in the mid-to-senior level leadership roles historically held by men.

Diversity reduces bias and improves work quality in organizations

The 2020 NCWIT report also found that women in the computing workforce are more racially and ethnically diverse than men in the field. As shown in the graphic below, there is a higher percentage of women with African American, Black, and Asian descent who hold computing roles than men. 

Graphic from the 2020 National Center for Women and Information Technology (NCWIT) report showing the racial composition between women and men with computer and information sciences (CIS) bachelor degrees in 2019. At all degree levels, the women earning CIS degrees are more racially and ethnically diverse when compared to men.

Workplace diversity plays a large role in reducing bias, which is especially critical in the computing field. According to a Boston Consulting Group (BCG) study, “Interpreting causal relationships and correlations in large data sets requires subtlety, and both humans and machine learning algorithms can occasionally ‘see’ patterns that lead to spurious, biased, or even downright dangerous conclusions.” A diverse team—whether by gender, race, ethnicity, sexuality, age, disability, and more—allows for various opinions and experiences to be considered when tackling projects.

Workplace diversity also improves the quality of work. A study done by Columbia University researchers Bo Cowgill and Fabrizio Dell’Acqua found that prediction errors were correlated within demographic groups, especially by gender and ethnicity. More diverse teams will reduce the chance for compounding biases, resulting in fewer errors.

While diversity reduces bias, it also leads to higher innovation revenue. Because people with different backgrounds and experiences often work through problems in different ways to come up with a variety of solutions, the odds that one of the solutions will be a financial success increases.

A chance to make a difference in the world

There are a number of ways that data science impacts the world, and according to the BCG study, this is important to women. The study found that 73 percent of women entering the data science and machine learning field prioritize tangible impact in their career choice, compared to 50 percent of men.

Graphic from the BCG study comparing the percentage of women and men STEM students who have a preference for working on applied problems with tangible impact. On average, the results show that women, including data science majors, place a higher emphasis on applied, impact-driven work than men do.

However, many women do not see data science roles as fulfilling their career goals. According to the same study, half of women instead see the data science field as “theoretical and abstract, focused on manipulating code and data with low impact and, by implication, low purpose.” Although there are probably many factors that contribute to this negative perception, the study cites the largest is the companies themselves. It is argued that companies are not communicating the important and meaningful role that data scientists play within their business, deterring applicants.

Data science is utilized in all industries, ranging from renewable energy, to healthcare, to public safety. Within these industries, the work of data scientists often has a tangible impact on the technology that will shape our future. In order to recruit women to data science roles, companies should showcase how data science is at the heart of effective decision making by highlighting the specific problems that data scientists solve in their organization. Bottom line, all industries stand to benefit from the experiences, perspectives, and skills that women in the field have to offer, and they must work toward better communicating with women in data science.

How to stand out in a competitive industry

If you have an interest in data science and want to stay competitive, enrolling in a data science master’s degree program may be the right next move for your career. You can start by asking yourself a few important questions before taking the leap, including which program is the right fit. Diversity in faculty expertise and perspectives is a critical component to consider before applying to a program. It’s important that you can relate to and feel supported by program faculty and staff.

UW Data Science strives to be inclusive

The gender gap within data science roles and leadership positions continues to be a pressing issue. Every organization can benefit from prioritizing diversity, equity, and inclusion initiatives within their internal culture and hiring processes. This requires conversations at all employment levels, from institutions granting degrees to CEOs discussing promotions to leadership positions. 

The UW Master of Science in Data Science program aims to create an inclusive environment for all. If you’d like to learn about graduates of the program, read about Venmathi Shanmugam, a modeling and simulations engineer working at the Veterans Affairs office, and Halee Mason, who is a lead data scientist at Cloud9 Esports, Inc. You can also learn about our diverse faculty members.

Have questions about the courses, tuition, or how to apply? Talk with an enrollment adviser by emailing learn@uwex.wisconsin.edu or calling 608-800-6762.

Data Science vs. Data Analytics: The Differences Explained

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If you’ve ever scanned job websites for roles in data, you’ve probably seen listings for data scientists and data analysts accompanied by job descriptions that sound quite similar. While the two fields are interconnected, data science and data analytics vary in scope, responsibilities, and goals.

One overarching similarity is that professionals in both roles use big data to solve problems and create improvements in an organization. The biggest difference, however, is how they interact with data. 

Data scientists often work with vast stores of raw data, working as investigators to create ways to analyze and model that data using statistical analysis and heavy coding. The goal of their work is to uncover the questions the data can answer. Data science often lays the foundation for further investigation. 

Data analysts leverage the modeling of the data scientist to create actionable and practical insights using a variety of tools. The work of data analytics involves using organized data to apply findings immediately.

Skills and Tools You’ll Need in Data Science and Data Analytics

There are some distinct differences between skills needed for data science and data analytics careers. However, there is also some overlap.

data science vs data analytics skills comparison in venn diagram
A Venn diagram highlighting the similarities and differences between the skills needed for data science and data analytics careers.

A Deep Dive into Jobs and Responsibilities

When looking at job opportunities, it’s important to not only look at the job title, but also the responsibilities, as the titles can overlap between data science and data analytics.

Some common job titles in the data science field are:

  • Data scientist
  • Data analyst
  • Data architect
  • Data mining engineer
  • Machine learning engineer
  • Hadoop engineer
  • Predictive modeler

Data science responsibilities often include: identifying opportunities for investigation, collecting data, predicting trends, cleaning and validating data, and communicating. To learn more about data science careers, read here.

Some common job titles in the data analytics field are:

  • Data analyst
  • Business analyst
  • Database analyst
  • Market research analyst
  • Operations analyst
  • Business intelligence analyst
  • Tableau developer

Here are some common data analytics responsibilities: exploratory data analysis, data cleansing, statistical analysis, and developing visualizations.

Salary Expectations

According to the U.S. Bureau of Labor Statistics, the median annual wage of a data scientist is $100,910. The 2022 Burtch Works Salary Report found that data scientists make on average between $90,000 and $275,000 annually, depending on experience level and managerial responsibilities. According to the same report, analytics professionals (referred to as artificial intelligence professionals in the report) can make between $105,000 and $275,000 on average, also depending on experience level and managerial responsibilities. For a more in-depth look at salary information, visit here.

Educational Advantage

One way to increase your salary is to earn an advanced degree, which is common in both fields. The Burtch Works study found that 93 percent of the data scientists and analytics professionals surveyed held an advanced degree.

A graph from the Burtch Works study showing the educational levels—including bachelor's, master's, and Ph.D.— of predictive analytics professionals and data scientists.
A graph from the Burtch Works study showing the educational levels—including bachelor’s, master’s, and PhD—of data scientists and analytics professionals (referred to as AI professionals in the report).

The 100 percent online UW Masters in Data Science prepares students for both data science and data analytics roles. Students not only learn technical skills they need to succeed, but they also gain knowledge in effective project management, leadership, and communication. 

Want to focus on data analytics? UW Extended Campus offers a virtual Data Analytics Bootcamp that can be completed in just 24 weeks. You will graduate from the program ready to apply your knowledge in the professional world.

Discover

The University of Wisconsin offers an online, 36-credit Master of Science in Data Science degree program. This data science master’s program will teach you how to harness the power of big data using the latest tools and analytical methods. Start your journey today.

Explore

Curious about what you’d learn in UW Data Science courses? See the curriculum.

Ask

Have questions about the UW Data Science program? Contact an adviser at 608-800-6762 or learn@uwex.wisconsin.edu.

UW Data Science Student Works Toward Master’s Degree to Expand His Future Career

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Although he has already earned two bachelor’s degrees—one in English and the other in information science and technology (IST)—Tim Drexler isn’t done yet. As a student in the 100 percent online University of Wisconsin Master of Science in Data Science (UW MSDS) program, Tim hopes to gain more programming and Big Data experience in order to take the next step in his career.

When he first graduated from UW-Madison with his English degree, Tim transitioned from a part-time role to a full-time one at South Central Library System, working in its delivery service. Over the past 20 years, Tim has moved up from delivery driver to delivery operations support manager.

“My job responsibilities have changed in many ways,” Tim said. “Three times a year, we complete a data sampling of our delivery volume. I am now responsible for collecting the data and putting it together in analysis spreadsheets. Working on these projects made me seriously think about how data science is something I would be good at.”

Tim’s untraditional entrance into the data science world continues to push him out of his comfort zone. On LinkedIn, he describes himself as a “systems-level analytical thinker and lifelong learner.”

In 2015, Tim began looking for a degree that would prepare him for a more technology-focused career, and he knew an online program would work best for his busy schedule. He considered Madison Area Technical College, but it offered programs with in-person class requirements that didn’t fit into his life. However, University of Wisconsin Flexible Option caught his eye, especially its 100 percent online IST degree. It felt like an attainable next step that worked with Tim’s goals and around his work/life schedule.

It took Tim only 13 months to graduate from the UW Flexible Option IST program with a UW-Milwaukee bachelor’s degree—a milestone that motivated him to consider pursuing a master’s degree in data science.

“UW Flexible Option was really good preparation for online learning in general,” Tim said. “I had experience within the learning system, and I knew how to motivate myself and manage my time, which are skills I continue to use in UW MSDS.”

RELATED: UW Flexible Option’s First Applicant Graduates with Information Science and Technology Degree

A Program Where Passion and Learning Converge

Every course in the UW MSDS program has been a huge learning opportunity for Tim. So much so, that he finds it difficult to choose just one as his favorite. From data mining and machine learning, to data warehousing and statistical methods, the UW MSDS curriculum touches on all aspects of a data science career.

“The courses are definitely a lot of work,” Tim said. “But I feel like I’m getting so much out of them.”

Tim’s favorite project in the program so far has been part of DS 740: Data Mining. Students use a dataset of their choice from Kaggle—an online source for datasets and programming/data analysis challenges—and analyze it by using methods covered in the course. The project allows students the freedom to find a dataset that piques their personal interests. Tim found a dataset from the Kepler Space Telescope that connected to his astronomy and physics curiosities.

“I put that dataset through a machine learning analysis process and then built algorithms that identified stars with potential planetary bodies orbiting them,” Tim said. “It was really interesting to be able to use real-world, scientific data to sharpen my skills.”

In fall 2019, Tim completed DS 745: Visualization and Unstructured Data Analysis, which directly related to his data collecting responsibilities at work. He said formatting the data is a continuous challenge, especially when it comes to communicating what the data represents.

“The data visualization course focused on summarizing and presenting data for non-technical people,” Tim said. “Now, I can go to my boss with a data plot or chart that illustrates how our delivery volume varies by weeks, months, and years. Then, I can work on an informative analysis that leads to meaningful action.”

RELATED: UW Data Science Professor Motivates Students to Look at Data Through Personal Lens

Supported for Success

Former UW Flexible Option Success Coach, Danielle Stertz

Tim’s transition from earning his IST degree through UW Flexible Option to enrolling into the online UW Master of Science in Data Science program, demonstrates the high-quality and continuity of service that UW Flexible Option and UW Extended Campus coaches and advisers offer. Tim is the first to vouch for the support he has received through both programs.

“I can definitely say that I wouldn’t have made it through the UW Flexible Option without (former Success Coach) Danielle Stertz’s help,” Tim said. “She was a great advocate and was always there to answer questions. I had some tough moments in that program, and I wouldn’t have pulled through without her support.

“When I’ve contacted (Senior Success Coach) Michael Paul for the UW MSDS program, it’s the same kind of situation. He’s always answering questions and getting back to students right away. It’s pretty amazing—the work that they do, especially to support people from a distance.”

UW Data Science Senior Success Coach, Michael Paul

Along with the support he receives, Tim also provides support to peers in his courses. A handful of students have noticed that Tim steps up to the plate within online class discussion boards and helps answer questions where and when he can.

To Tim, he sees this as a way of putting himself in others’ shoes.

“I don’t necessarily have expertise per se, but if there’s something I can answer right away, then I don’t mind giving it a shot,” Tim said. “I try to look at it as if I had a question that I posted. I would want it answered sooner rather than later, even if it wasn’t quite right, just to spark my thinking process. It’s a way for me to help others—and myself—to get unstuck.”

Ready to Take the Next Step

With more than half of the UW MSDS program’s courses complete, Tim is optimistic that he is becoming well-prepared to move into an entry-level role as a data analyst or similar position. He views earning his master’s degree as a major step in his career and one that he is eager to see through.

“I’m coming from a field where I have no real technical background, and I’ve been fortunate to have completed a lot of classes with other students with database administration and other data science experience,” Tim said. “I’m learning a lot just from interacting with them and understanding all the ways I can specialize in different industries.”

For Tim, the flexibility, affordability, curricula, and support within the UW Flexible Option IST and UW Data Science programs made his choice to go back to school while working full-time possible. Furthermore, Tim embodies the Wisconsin Idea—investing in himself to advance his skills in order to impact his future, improve processes at his work, and to connect with the greater community.

When asked for his parting advice to prospective students, Tim is honest about his pacing throughout both programs:

“It’s important to try to plan your class schedule so you don’t overload yourself too much in any one semester,” Tim said. “One thing I was worried about right away was having too much to do. So, I started the program with a smaller course load to get my feet wet. Do what makes the most sense for your strengths and life. And know that you have support along the way to keep you going.”

Tim has since graduated from the UW Data Science program and is now a data services consultant at South Central Library System. 

What’s Next?

Start exploring how the UW Master of Science in Data Science online degree program can push you to new career heights. Have questions about the courses, tuition, or how to apply? Talk with an enrollment adviser by emailing learn@uwex.wisconsin.edu or calling 608-800-6762.

UW Master of Science in Data Science is a collaboration of several UW System campuses. Tim earned his degree from UW-Oshkosh.

UW Data Science Professor Motivates Students to Look at Data Through Personal Lens

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When Abra Brisbin was earning her undergraduate mathematics degree from Carleton College, she wanted to apply math and data to areas that made an impact in the real world. To do that, she earned her Ph.D. in applied mathematics from Cornell University, where she focused on statistical genetics—understanding how genetic variations influence people’s health.

In the next two years, Abra completed a postdoc at Mayo Clinic in Rochester, Minnesota, and then moved into her current role as an associate professor in the mathematics department at the University of Wisconsin-Eau Claire. Additionally, she co-develops and teaches courses in the 100 percent online University of Wisconsin Master of Science in Data Science, including DS 710: Programming for Data Science and DS 740: Data Mining.

In the following Q&A, Abra shares what drew her into the world of data science, what motivates her to be a teacher in the UW MSDS program, and how she helps her students gain the skills they need to be successful in the field.

What drew you into the world of data?

I think one of the great things about statistics and data science is that you can analyze data from a wide variety of different fields.

When you find an interesting data set, you can figure out what there is to learn from it. For example, I’ve worked with students on research projects involving crime rates in Eau Claire or students who have analyzed factors that influence housing prices in the city—which both have a personal importance beyond the numbers.

Data set from DS 740: Data Mining

Why did you become a faculty member of UW MSDS?

It was an opportunity that came up through my connection with Alex Smith—the chair of the mathematics department at UW-Eau Claire. He was getting involved in developing the UW MSDS curriculum and it was really interesting to me. It sounded like a way where I could have some influence over designing these new courses and to really focus on the things that I think are the most important about programming for data science and machine learning.

What are those important aspects of data science, machine learning, and programming?

I think the problem solving aspect is really important because it’s not just simply following a series of steps. It’s thinking where you use both logic and creativity to come to a solution.

The willingness to learn is also huge. As a professor, I can’t possibly teach all of the algorithms that students might need to know when they go out to do data science in their careers. I make it a point to demonstrate how I figure things out and learn more about how various data science methods work, so that students will be prepared to teach themselves in the future when they are out of a structured learning environment.

What is your favorite part of teaching your UW MSDS courses?

The final project in DS 740: Data Mining is really fun because the students can choose whatever topic they want to analyze. They start by choosing a data set from Kaggle—an online source for data science data sets, programming challenges, and data analysis challenges.

Then, they analyze the data using two of the methods that we cover throughout the course and they come up with their assessment of how the data addresses a question that would be of interest to their target audience and which of the data analysis methods they’d recommend.

This project is when students have a chance to branch out into the data set that’s interesting to them, which can show off their personality and learning style. It’s fun to grade, because I get to read about all of these different data sets that I may not be familiar with.

Data set example from DS 740: Data Mining

How would you describe your teaching style when it comes to online learning?

I’ve structured the courses I teach so that each lesson fits into one week of the semester (although the pace is faster in the summer). Most lessons have some reading and one or more short video lectures, where you can hear my voice or the voices of my co-instructors as we talk through slides or demonstrate an analysis on our computers. Additionally, lessons have some low-stakes practice problems where you can get hints and try them as many times as you want. Then, you have weekly homework, which gives you hands-on experience with implementing the methods discussed in that lesson.

The interactive part of the courses comes from our discussion board and online office hours. Our course discussion board is very active with students asking questions, helping to answer each other’s questions, and even discussing related topics, such as sharing interesting news articles they read about data science. I check the discussion board twice per day, so students get feedback quickly.

I typically have online office hours two or three times a week, once or twice during business hours, and once that’s either in the evening on a weekday or at some time on a Saturday. The goal is that as many students as possible will be able to attend at least one of those times. It can be a phone call or you have the option of sharing your webcam so we can see each other. There’s also a chat window where students can enter questions.

When I’m answering questions in office hours, I can share my screen and demonstrate examples of code or pull up slides from the lecture to show how a question connects with the material that was covered in the class that week. Students can chime in with follow-up questions or help answer each other’s questions. We record office hours and post links to them within the discussion board, so students who can’t attend office hours can still view what was discussed.

What advice do you have for current and prospective UW MSDS students?

Be excited about problem solving and learning about all of the aspects of data science!

Also, be aware that master’s-level courses are challenging, even if they’re only three credits. Students who are working full-time jobs might be better served by taking just one course a semester. Some students who are very motivated can do more than that, but taking three courses in a semester while also working full-time is a very, very heavy load. It’s important to find that balance that works best for your life.

Why should prospective students consider UW MSDS?

Our program offers a strong balance of the quantitative rigor that students will get from programming and data mining courses along with the business acumen that they get from courses such as DS 735: Communicating About Data and DS 760: Ethics of Data Science.

I think the fact that this program is online makes it really good for students who are currently working in a job that uses some data science and those who want to advance their careers by getting a degree. This program can help them get to the next career step they are aiming for.

Want to learn more about how expert faculty members, like Abra Brisbin, teach, connect, and prepare UW Master of Science in Data Science students for exciting careers in the field? Check out the program’s curriculum or contact an enrollment adviser at 608-800-6762 or learn@uwex.wisconsin.edu.

6 Questions to Ask Before Pursuing a Master’s Degree in Data Science

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Face it, you’ve been on the fence about going back to school for a while now. After Googling master’s degree programs in data science here and there, you still feel overwhelmed about deciding if one is better than another. When there’s countless sources of information tugging you in every direction, it’s best to gather your bearings and figure out the most important details you need in order to guide you in the right direction.

Luckily, we’ve done the legwork. Below are the six most important questions to ask before you begin your application to a data science master’s degree program. Think of this as a mental checklist to help you cross off crucial considerations before taking on your educational future:

1. Do I have an interest in or want to strengthen my problem solving, data management, and research skills?

When you have an interest in data science practices and want to grow your hard and soft skills, enrolling in a data science master’s degree program is a promising endeavor. In fact, 2022 Lightcast research shows that data analysis and programming languages are frequently listed in data science job postings, while management, problem solving, and communications round out the preferred soft skills:

A chart showing the top specialized skills seen in data scientist job postings.

A chart showing the top common skills seen in data scientist job postings.

Employers want data science master’s degree graduates to be well-rounded professionals, capable of tapping into the technical side of a role while effectively understanding and communicating data to drive actionable insights. With this in mind, it’s to your advantage to find a master’s degree program that not only prioritizes the hard skills of data science, but also the soft skills. When researching program curricula, look for courses such as DS 735: Communicating About Data, DS 760: Ethics of Data Science, and DS 780: Data Science and Strategic Decision Making—all of which expand on skills that are not only needed, but also demanded in today’s data science roles.

2. What are my career goals?

Venmathi Shanmugam, UW Data Science graduate

If you’re looking to be part of a dynamic team in charge of solving real-world problems, or if you want to efficiently draw conclusions from data to better inform actionable business strategies, a master’s degree in data science can set those career goals in motion.

Whether you strive to be a data analyst, database administrator, data architect, strategic business and technology intelligence consultant, or another data-focused professional, the impact of your work can be substantial. For example, Venmathi Shanmugam, a recent graduate of the University of Wisconsin Master of Science in Data Science online program, is the Modeling and Simulations Engineer at the Veterans Affairs office in Austin, Texas. In her role, she manages large amounts of government data pertaining to veterans healthcare and finance. She also holds responsibilities in the supply chain division of her department—using data to positively impact patient needs.

3. Who teaches the data science curriculum?

When enrolling in a graduate school program, you want to feel confident that you are learning from qualified experts in your desired field. A strong data science master’s program is rooted in an interdisciplinary approach, not siloed off to one academic school or department. Diversity in faculty expertise and perspectives is a critical component to consider before applying to a program. Don’t hesitate to research potential faculty members’ background, education, and recently published research studies.

UW Data Science faculty members

The UW Data Science online program is a prime example of an interdisciplinary approach in action, where students learn from faculty members across six UW System campuses. With advanced degrees in mathematics, marketing, computer science, philosophy, management, statistics, and rhetoric and computer composition, graduate students receive the direct benefits of working and learning alongside UW faculty who are driven to grow and advance from every corner of the data science profession.

4. Does the degree program provide a networking community fueled by collaboration?

It’s important to consider how a data science master’s degree program sets you up to connect with industry leaders during your time as a student and after you graduate. Look for programs that feature an advisory board of data science professionals across business sectors. This collaboration of individuals shows that the program is supported by outside experts who can help you connect with future employers and/or mentors.

The UW Data Science online program boasts an impressive advisory board, where recognized data science leaders have the opportunity to shape the program. UW Data Science Advisory Board members can also sponsor capstone projects, plugging students into real-world data science settings where they draw upon their skills and grow from hands-on experiences. Currently, the UW Data Science Advisory Board includes data science professionals in the retail, banking, software programming, manufacturing, state government, insurance, transportation, staffing, and medical fields.

5. Do I have the time to earn a graduate degree?

For some working adults, it is too time consuming to earn a master’s degree through an on-campus program. Traveling to and from a campus throughout the week to sit in on hour-long lectures can complicate the balancing act of work and family responsibilities.

data science

If this is your reality, then pursuing an online graduate degree might be your best option. But, not all online degrees are the same. Make sure to thoroughly research an online degree’s requirements and consider how much flexibility you will need when it comes to lectures, readings, and coursework. 

UW Data Science is a smart choice for busy adults who want to advance their careers, or make a career change. Offered 100 percent online, you can study and complete coursework whenever and wherever you have an internet connection. Courses have no set meeting times, and you never need to come to campus.

6. Is the program accredited and respected?

When deciding to pursue a master’s in data science, you want to be sure that future employers will value the degree-granting institution you’ll graduate from. There’s no question that you can earn a graduate-level education from almost anywhere in the country and world, so how do you know which programs are worth your time and money? Look for degree programs that are accredited by regional and national accreditors, such as the Higher Learning Commission (HLC). 

According to the HLC website, in order to be accredited an educational institution must 1.) have a clear and publicly articulated mission, 2.) conduct actions responsibly, ethically, and with integrity, 3.) provide high-quality education, no matter where and how offerings are delivered, 4.) evaluate its student learning effectiveness and promote continuous improvement, and 5.) have resources, structures, and procedures that support the institution’s mission. 

The UW Data Science program is HLC accredited, signifying that its students receive a high-quality education led by faculty who are committed to staying up-to-date with the expanding data science field. Plus, UW is known and respected worldwide, helping graduates of the UW Data Science program stand out to employers. As a trusted and valued institution, a UW degree can help graduates accomplish their career and personal goals.

So, you’ve gone through all six questions, what have you found?

With an expert-led curriculum, a 100 percent online format, and a recognized and respected UW degree, now is the time to see where the UW Master of Science in Data Science online program can take you.

Have questions about courses, tuition, or how to apply? Talk with an enrollment adviser by emailing learn@uwex.wisconsin.edu or calling 608-800-6762.

From Dentistry to Data Science: A UW Grad’s Career Journey

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In May, Venmathi Shanmugam and her five-year-old daughter shared a special milestone.
They both received diplomas—one graduated from kindergarten while the other from the University of Wisconsin Master of Science in Data Science online degree program.

A couple days before crossing the stage at UW-Eau Claire, her home campus for the program, Venmathi reflected on the major accomplishment:

“When it comes to putting your heart and soul into something, you need to go for it,” she said. “People can say going back to school is impossible. I have a family and a busy, full-time job. If I can do it, anybody can do it.”

Venmathi is currently the Modeling and Simulations Engineer working at the Veterans Affairs office based in Austin, Texas. This dual role includes data engineering and data scientist responsibilities where she works with large amounts of government data pertaining to veterans healthcare, finance, as well as the supply chain division.

Being in the data analytic and data science profession for about seven years now, Venmathi has taken on previous positions in business and IT consulting, statistical data analytics, and clinical programming. But before diving into the data science world, she was on a different path.

“Ten years ago, I was practicing dentistry in India,” Venmathi said. “But the idea of expanding my scope was always at the back of my mind. As a healthcare professional, I needed to work with and understand data. When I reviewed my patients’ medical history before any treatment, I saw patterns in how oral health affected their overall personal health and started getting curious. It was during that time that I realized data science was something that would help me connect all the dots and was an area I didn’t want to miss out on exploring.”

 A Supported Online Degree Experience

After she moved to the U.S., Venmathi completed online certifications in statistics, healthcare informatics, programming, bioinformatics, and more to help bolster her knowledge as she gained experience in various data science roles.

Growing from one job to the next, Venmathi was always motivated to take on new challenges. Already comfortable with online education through her previous trainings and certifications, Venmathi decided that her next step was to get a formal data science degree.

“I took about six months doing course research on every single university that offered data science,” Venmathi said. “The UW Data Science curriculum had a little bit of everything, starting from the very basics and establishing a foundation to progressively dive into more deeper challenges like machine learning, robotics, advanced programming (Hadoop, Spark, Amazon Web Services), and advanced statistics. When I learned about how the degree was flexible and online, I felt like it was meant to be!”

Venmathi has not forgotten how she felt at the beginning of the program. A feeling that she knows many prospective students might be dealing with.

“I was really worried about what I should expect and if I would even be prepared to go back to school,” she said. “I was doubting myself and wondered how structured the courses would be. I wasn’t sure if I had the principle and drive to see a full degree through.”

Venmathi’s fears were quickly proven unfounded once she jumped in. She soon got into a routine, with readings, coursework, and other tasks due on the weekends. She loved having deadlines to work against. They were tough challenges with her busy life, but they also brought structure and fun into her learning experience. By having the flexibility to take lessons when her schedule allowed, Venmathi felt like she was accomplishing tasks and learning something new every week.

“In other online courses I didn’t connect with faculty unless it was for quarterly reviews,” Venmathi said. “When I started the UW data science program, I had a lot of questions, and I found that all my professors, my student success coach, Michael Paul, and my student advisor, Dr. Alex Smith, were always there for me. I should really thank all of them for making my time in the program so positive.”

Taking on a Challenging Capstone

Venmathi wanted her capstone to be the culmination of everything she learned. So, she decided to push past all of her comfort zones and pursue a challenging topic involving a combination of AI automatic speech recognition, voice analytics, facial recognition, Natural Language Processing (NLP), advanced Python, and deep learning techniques.

The result was a comparative case study and demo between an Automatic Speech Recognition System (ASR) technology—currently implemented in smart devices—and an Advanced Multimodal Automatic Emotion Recognition System that could potentially combine voice, face, and emotion.

Inspired by her successful projects in
DS 740: Data Mining that focused on the use of NLP, emotion recognition, and sentiment analysis from live social media posts, Venmathi began to research and experiment more on the futuristic topic.

“When a user talks to an AI product like Siri and says ‘I’ve had a long day,’ the AI either usually apologizes for not understanding or gives you search results on what that phrase means,” Venmathi said. “You get a little annoyed because the supposedly ‘smart’ device is not smart enough to capture your feelings or tone of voice, unless you spell it out. You keep repeating things, and there is always going to be problems with understanding different accents.”

With the right combination of voice, text, and facial recognition, Venmathi believes the AI could pick up on the stress in the user’s voice, see the frown on his or her face, and launch into a more helpful response.

Venmathi faced a lot of road bumps with the computing and deep learning aspects of her capstone. As she wrapped up her project, she knew there was a lot more research and testing to be done—especially with model tuning and improving fusion accuracy. However, she was happy with how she was able to successfully prove her target goal: that a multimodal emotion recognition system would add measurable improvement to the accuracy rate of the current ASR system.

“Professor Ethan Christensen, who reviewed the capstone project, really appreciated me,” she said. “He was a huge encouragement and recommended that I publish my capstone as a research paper. I am planning on making that happen.”

From One Accomplishment to the Next

Even before graduation, Venmathi could put her data science coursework into action.

“I have a brand new portfolio, including knowledge and skillset on all cutting-edge technologies and tools like NLP, deep learning, AI, Hadoop, Python, R, SQL, Spark, Pig, Scala, and Java, and I find myself becoming useful to my team more and more from everything I learned from the UW courses,” Venmathi said. “It’s a really good feeling when you actually apply your learned skills at work and know that your project can get you a lot more than good grades.”

Now that she has obtained a master’s degree in data science—graduating with a 4.0 GPA—Venmathi feels that she can understand, communicate, and execute on all levels in her data science and data engineering roles— effectively coordinating business, tech, and engineering needs.

Next up, Venmathi has her eyes set on an executive doctoral program in health informatics and leadership and is excited to move from one successful educational experience to another. But for people who are still wondering, like she did, if the
UW online master’s in data science is worth the leap, Venmathi hopes readers take the following words to heart:

“Encouragement or discouragement comes from within ourselves,” she said. “Life and big decisions, like going back to school, are always going to be a challenge—whether it’s today or tomorrow. You will be able to do this, whatever the case may be.”

Start exploring how the UW Master of Science in Data Science online degree program can push you to new career heights. Have questions about the courses, tuition, or how to apply? Talk with an enrollment adviser by emailing learn@uwex.wisconsin.edu or calling 608-800-6762.

UW Master of Science in Data Science is a collaboration of several UW System campuses. Venmathi earned her degree from UW-Eau Claire.

6 Surprising Degrees That Set You Up for Data Science Success

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Right brain v. left brain—which one do you prefer? It’s a common assumption that more left-brain professionals are taking the lead in science and math-dominated fields. Comfortable with flexing their analytic muscles, pursuing a data science career—one of the top five jobs in America according to Glassdoor—seems like well, a no brainer.

But what does this mean for the traditionally right-brain folks? Those who find strength in creativity, imagination, and intuition shouldn’t write off a data science career so quickly. Having a non-technical undergraduate degree can actually complement a master’s degree in data science. Although data scientists do rely on math, programming, and more technical skill sets, a data science career isn’t all about numbers. Often, data is gathered from human behavior. As a result, coming into the data science field with little-to-no prior STEM education can give you a more holistic view of how data can evolve and expand into the future.

The need for data scientists reaches into virtually every industry, providing numerous career opportunities. The following undergrad degrees might seem as right-brain areas of studies. However, they could set you up for data science success:

Sociology

What is it?
Defined as the scientific study of human groups, a sociology degree focuses on understanding how a society functions through the lens of social constructs that affect individuals and entire populations. Sociology has many branches including education, crime, family life, organizations, race, social class, and more. The common goal of sociology is to see the world differently and understand that not everything is what it seems.

How does it relate to data science?
Data is the result of asking questions, and sociology majors are no strangers to examining why something occurs. If you have a goal of advancing contemporary humanity and have an itch to use data as a tool in the process, sociology and data science can be an advantageous coupling of what may otherwise appear as dissimilar interests. By collecting survey data, sociology-driven data scientists seek to study social phenomena, allowing space for both numbers and creative questions to lead their research. The expansion of Big Data is promising for new areas of social research, such as digital behaviors, longitudinal analyses, and network analysis beyond household connections.

Psychology

What is it?
Simply put, psychology is the study of the mind and behavior. A common assumption of a psychology career focuses on professional therapists who work with a rotation of patients with different needs. However, psychology is a diverse field that touches human development, sports, health, social behavior, cognitive processes, and more. Would you be surprised to learn that data plays an integral part in psychology? Similar to sociology, psychology research aims to answer complex questions regarding human behavior.

How does it relate to data science?
Data science skills, such as research methods and statistics, can help professional psychologists understand data findings and turn them around to drive positive change in patients’ lives. Additionally, by developing evidence-based strategies, those with a psychology background can advance best practices for individuals with learning disabilities. The possibilities of a psychology and data science pairing are expansive and have the potential of truly changing lives.

Public Policy

What is it?
Highlighting social science fields such as economics, public management, and sociology, an undergraduate degree in public policy examines issues within governmental administrations and operations. Adapting theories, research, and models to practice, public policy focuses on how cultural norms, circumstance, and other human differentials affect policy making.

How does it relate to data science?
Research data heavily influences public policy models, which can impact hundreds of thousands of constituent lives. In some states, city government has expanded to include data teams that use civic data to serve communities more effectively. Major questions that a public policy and data science approach can begin to answer include: Can we target outreach and intervention to those at risk of poor health outcomes? Where are there unreported incidents of food poisoning? How can we predict major bridge problems before they happen? How can social media data help identify public safety issues?

Philosophy & Ethics

What is it?
With a degree in philosophy and ethics, graduates become well-versed in considering the fundamental questions about who we are. By examining historical and present-day philosophical thought, this area of study strengthens critical thinking, persuasive writing, and effective arguing. Subjects such as political philosophy, metaphysics, logic, philosophy of mind, and more are common in coursework, preparing graduates for careers that value strong communication and problem solving.

How does it relate to data science?
Although philosophy is a humanities degree, its approach and skills can easily transfer into a data science role. One data science manager who first earned an undergrad degree in philosophy, notes that his philosophy studies prepared him for the hypothesis-driven, logical practice of data science. A philosophy-data science path also spotlights the timely issue of data use and security. As more companies come under fire for data breaches and misuse, data scientists are tasked with an ethical burden of how to handle data. Having a philosophy background can better position data science professionals to be more involved in ethically sourcing, securing, and verifying complete and accurate data.

Journalism

What is it?
The world of journalism is no stranger to change. With the decline of traditional print newspapers and magazines and the swift pivot to digital and social media as main sources of breaking news, reporters now need to be at least 10 steps ahead. Dwindling attention spans mean audiences are distracted, requiring journalists to think outside the box to bolster engagement. While the core principles of journalism stay true: serve the public with fact-checked, credible, objective information—the delivery has changed. And, that is where data journalism steps in.

How does it relate to data science?
Journalism, digital media, and data science are all connected. As Big Data evolves in languages and processes, data scientists must understand digital media technologies that provide a platform for their work. Next, it’s critical for journalists to stay abreast of data security, collection, and usage issues that affect the public—knowledgeable reporting comes from plugging in and understanding the ins and outs of the data science world. As a result, journalists with their drive to learn, understand, and inform, can bring all of those skills into a data science role. In effect, having a journalist’s mindset in a data-fueled world can help piece together the bigger picture of how data touches nearly every part of our lives.

Marketing & Business

What is it?
Advertising, promotion, marketing communications, research, targeting, consumer behavior, and other courses prepare a marketing graduate to land a variety of roles. Marketing and business degrees often cross paths, because having a successful business means also maintaining a strong marketing presence. However, the two disciplines cannot be nearly as impactful without understanding data, often in the form of ROI or digital analytics, such as tracking visits, clicks, and conversions on websites and social pages.

How does it relate to data science?
Human behavior, which can be recorded and interpreted through data, is a critical driving factor behind why a marketing or business endeavor flies or flops. In turn, data companies rely on marketers and business professionals to invest in their tools and services, creating a symbiotic relationship flowing with information. Earning a data science graduate degree benefits marketing and business analysts who are looking to take a deeper dive into how data can better inform and predict their brand strategy and campaigns. Having the ability to review and understand data and then the creativity to turn those insights into an optimized branding push is an invaluable skill.

What’s Next?

Do you have a degree in sociology, psychology, public policy, philosophy, journalism, marketing, or business and are intrigued in how data science can expand your professional future? The UW Masters of Science in Data Science online degree can be the bridge between your non-technical education and your next career move.

Earning a master’s degree in data science opens the door to diverse and exciting work with Big Data, and a promising career outlook.

Contact an enrollment adviser to learn about transferable work experience, recent prerequisite coursework, and other admission requirements. Call 608-800-6762 or email learn@uwex.wisconsin.edu.

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