Experts Weigh In On Current Job Market Trends

What experience really stands out on Data Analyst resumes?

Pavel Chernyavskiy Ph.D.: Good software skills (R, Python, C++, etc.) are pretty standard at this point, so applicants should aim to differentiate themselves in other ways. I like to see applicants demonstrate evidence they have been involved in a project: for undergraduates; this might be a poster presentation or a capstone project; for graduate students, this might be co-authorship on a published manuscript thesis work.

I value teaching experience since it usually implies that the applicant is a good communicator who can figure out how to manage a classroom and work with a range of stakeholders.

What Data Analyst skills would you recommend for someone trying to advance their career?

Pavel Chernyavskiy Ph.D.: Statisticians with subject-matter expertise tend to be more in-demand, all else being equal. For example, quantitative biologists, statistical geneticists, bioinformaticians, industrial statisticians can all be thought of as "statisticians with subject-matter expertise," at least in my opinion. With that in mind, if an applicant can develop their knowledge of a particular area of application during their gap year, it should help them in the job market.

What technology do you think will become more important and prevalent for Data Analysts in the next 3-5 years?

Pavel Chernyavskiy Ph.D.: It is always dangerous to make predictions with technology since things rush. My thought is that access to High-Performance Computing - a centralized high-powered computing cluster - will become more streamlined. This should encourage users to run their complex computing tasks remotely and use their machines for rapid testing and development.

What general advice would you give to a Data Analyst?

Joseph Byrum: The next revolution will happen when every aspect of a business, from top to bottom, is designed with AI and OR in mind. Call this new construct the intelligent enterprise. A joint cognitive system view is the first step in creating the intelligent enterprise - a large, complex organization with global distribution of its resources and processes run by people who make consistently excellent adaptations to rapid changes in the world. They also share the execution of these rapid adaptations seamlessly across the entire organization without loss of consistency and coherence.

What type of skills will young Data Analysts need?

Joseph Byrum: -Quantitative skills
-Complex problem solving
-Critical thinking
-Judgment and decision making
-Strong writing and composition skills
-Creativity
-Project and People management
-Emotional intelligence
-Adaptability - Cognitive flexibility

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Joseph Byrum: Everywhere. Supply Chain, Health Care, Finance, Pharma, Technology, Defense, Cyber, ect..

What type of skills will young Data Analysts need?

Michael Ettlinger: Analytic, communications, and political skills are all sought after. A graduate need not be highly skilled in all three to be successful. Still, even a pure public policy analyst will be more successful if they understand the political environment with which their analysis will interact and effectively communicate their research. Similarly, a communicator, or one who operates mostly in the political realm, may not need to be able to do high-level analysis. Still, they need to understand research and tell useful comments from the lousy study.

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Michael Ettlinger: Increasingly, jobs in policy analysis are not location-dependent. Even federal government agencies, even before COVID-19, but particularly now, are offering remote work options. There are state and local government jobs, and jobs that relate to them, in every place in the country. Larger states tend to have more massive policy infrastructures, even relative to their size, than smaller states, thus having more opportunities. There are, however, jobs in this field everywhere.

How do you envision technology impacting Data Analysts in the next 5 years?

Michael Ettlinger: The use of large data sets in public policy decision-making will continue to advance as the tools become more powerful and more accessible.

What type of skills will young Data Analysts need?

Dr. Pratim Datta Ph.D.: I am thinking and problem-solving. I find young people often shy or scared to think hard. It does not work when a person (student) wants a one-size-fits-all solution to all problems. They have to have the guts to think and take risks, and risk-taking is rare these days, as is thinking. No technical skills matter if a person cannot or will not believe it.

Next is collaboration. No one works alone (except maybe artists, writers, etc., but they have agents, so even they do not work alone. In business, everyone works in teams, so all graduates must know how to work with others. That means good communication skills, and that means being straight-forward and entirely honest with all peers. If people cannot contribute to a team, they have no future in business.

Next is self-learning. Graduates must be interested on their own, without a mentor or teacher telling them what to consider next. The rate of technological change is so fast that waiting to be told what to do next is a non-starter. No textbook can be written fast enough to relate to new trends. Successful young people learn what is being developed and master it independently with assistance from no one. No one can hide, and the business expects high-performance from everyone.

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Dr. Pratim Datta Ph.D.: Yes and no. It depends on the type of work. If you want to work in hi-tech and create new technology products, move to Seattle or Silicon Valley. If you're going to work in business, go to a mid to large city and work for established technology departments.

The availability of job opportunities is exceptional. The US Bureau of Labor Statistics, Labor Statics!, is an excellent resource of what jobs are hot and what you need to do to get into specific fields.

The bottom line, technology fields are hot and will remain so. Software, not hardware, is the "steam engine" of the 21st century.

How do you envision technology impacting Data Analysts in the next 5 years?

Dr. Pratim Datta Ph.D.: Technology developments allow businesses and other organizations to try new things that may enhance their business success. The field of "information sciences" is not what is being impacted; it is the users of technology being affected because technology developments give them more significant opportunities to reach further, grow business and extend competitive advantage.

What matters to business is hiring people who can help them use information technology effectively to promote success for the company.

A word of caution: technology developments have had an impact since the dawn of civilization. When a new technology is introduced, it becomes common knowledge almost immediately (even old technologies like writing, the inclined plane, printing press, the telegraph, the steam engine, etc.) are quickly mastered by all, but those who understand how society may benefit from the use of the technology are the people who succeed.

Technology is not an end in itself. It is a vehicle for the future.

What type of skills will young Data Analysts need?

Feryâl Alayont: A mathematics major helps students develop problem-solving, critical thinking, mathematical modeling, and communication skills. Graduates will need to know how these skills are applied in real-world contexts, from communicating their results to a non-mathematical audience to identifying the data or modeling problem behind the real-world issue they are working on. Data analysis and programming skills will be essential as businesses and organizations collect more data through various means. Finally, with the workforce becoming global, diverse, and collaborative, graduates will need teamwork skills to successfully navigate working in the world of varied and international teams regularly.

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Feryâl Alayont: Larger cities are more likely to provide work opportunities for a mathematics major. The companies with the capacity to employ data analysis processes in-house will be the mid-to-large size. However, a resourceful math major with a flexible employment approach can find meaningful and well-paying jobs in any area.

How do you envision technology impacting Data Analysts in the next 5 years?

Feryâl Alayont: As data collection, storage, and analysis become more efficient and affordable through various technologies, more companies and organizations will start leveraging data analysis and machine learning in their decision-making processes. As a result, learning programming and data analysis tools are a must for math majors. Furthermore, with these tools evolving rapidly, the graduates will have to be ready to learn and relearn new concepts and technology constantly. Even for the more traditional math career route, such as being an actuary, graduates should expect rapid changes in their careers.

What type of skills will young Data Analysts need?

Hongshik Ahn: Mastery of programming languages, analytical skills

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Hongshik Ahn: If this is about geographical location, then East Coast, West Coast, or Texas will be the right places.

How do you envision technology impacting Data Analysts in the next 5 years?

Hongshik Ahn: There will be a huge impact, especially by artificial intelligence and remote learning.

What type of skills will young Data Analysts need?

Zhixin Wu Ph.D.: Problem solving skills, analytical skills, self-learning ability, and good communication skills.

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Zhixin Wu Ph.D.: (1) Insurance Companies or Actuarial Consulting Firms. Students can work as an actuary analyst or work in the field of underwriting and risk management.
(2) Banking and Investment, doing investment and accounting or work as a financial analyst or market research analyst
(3) IT companies, as a programmer or data scientist
(4) Pharmaceutical companies as a statistician
(5) K-12 Schools as a math teacher

How do you envision technology impacting Data Analysts in the next 5 years?

Zhixin Wu Ph.D.: Technology will have a significant impact in the field of Actuarial Science, Data Science, and Statistics, in the next five years. Big data and the potential uses of this information, have been receiving a significant amount of attention in recent years. Industries such as technology, banking, and insurance have fundamentally changed after experiencing an analytics revolution around using big data to make better business decisions. Traditional tools and infrastructure cannot handle large data set efficiently. Predictive analytics is the branch of advanced analytics which is used to make predictions about unknown future events. It uses many techniques from data mining, statistics, machine learning, and artificial intelligence. Students are expected to master the data analysis skills by using some type of software for future better job opportunities.

What type of skills will young Data Analysts need?

Margaret Cheney: A combination of applied mathematics training with training in other related disciplines will likely be especially attractive to employers. Knowledge of statistics and computer science is very useful too. Experience doing internships also makes math students much more attractive to employers.

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Margaret Cheney: Most urban areas have opportunities. The particular field of application (the related discipline mentioned above) may be associated with certain areas of the country with concentrations of the particular industry.

How do you envision technology impacting Data Analysts in the next 5 years?

Margaret Cheney: The pandemic is showing that remote work is a viable option, and mathematical work tends to be especially easy to do remotely. Employers are still hiring, even throughout the pandemic.

What type of skills will young Data Analysts need?

Mark Gibson: The skills graduates need when they enter the workforce are higher-level cognitive skills. Critical thinking and problem-solving are the most important. Being able to analyze and interpret data is a crucial part of this. Economics is designed to equip students with these skills.

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Mark Gibson: Economics isn't meant to prepare graduates for a particular field after graduation. Rather, it imparts a set of analytical and quantitative skills, that are highly valued, in a number of fields, including finance, banking, data analytics, government policy, and law.

How do you envision technology impacting Data Analysts in the next 5 years?

Mark Gibson: Technological progress increasingly favors high-skilled workers, particularly those with superior analytical and quantitative skills. Economics graduates need to stress their broad-based strengths in these areas, which enable them to adapt to changing technology.

What type of skills will young Data Analysts need?

Christopher Wooldridge: In the surveys we have completed, there are some general reoccurring themes 1) pass a drug test, 2) show up on time, 3) be able to communicate (speak and write), 4) be able to think critically, and 5) tell the truth. In addition to those, the education and experience level of graduates is very important. This field continues to grow, and the competition for these positions will become more intense.

Those that can gain experience through internships and other experiential learning opportunities, while also working on an academic credentials, will have a head start for entry into this field. Both of those were considerations when Murray State University established the Masters in Economic Development as well as a certificate in ED to provide that credentialing for students in the region and beyond.

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Christopher Wooldridge: Yes, there are, depending on which career path of economic development one chooses. Geographically speaking, the South and West regions of the United States seem to be growing the fastest. Texas seems to be experiencing a tremendous amount of growth in many cities, including Austin, McKinney, and Houston. Outside of Texas, looking at fast-growing metropolitan areas and the surrounding areas, is a start for those seeking to be part of large, rapid city growth.

Cities such as Nashville, Louisville, Charlotte, and Jacksonville City. However, the rural areas of the Midwest and South can also offer great opportunities as populations begin to shift to rural areas from metropolitan areas, due to changes in demographics and psychographics (some CV19 driven also). A person seeking a slower pace and possibly a higher quality of life can find opportunities to assist and grow rural areas through economic development. One should look at where they want to live and can begin that by using census.gov to learn more about the area.

How do you envision technology impacting Data Analysts in the next 5 years?

Christopher Wooldridge: Economic Development requires so many different skill sets. Some of those skills involve obtaining, analyzing, and applying data and information. Technology that develops and improves in those areas will be very important to the economic development professionals' success. The competition will drive the need to be able to "do more, better and faster" in regard to data and information, to grow a community through economic development. And technology, hopefully, will support the other, very important skill set, in economic development ... that being relationship building.

What type of skills will young Data Analysts need?

Xingye Qiao Ph.D.: Computing skills are becoming increasingly important, as statistics embraces the data science revolution. Students need to be able to program (using R or Python or some other language), take the data from the web, reshape it, manipulate it to allow easier downstream analysis, and be able to communicate the finding professionally.

All these are, of course, on top of statistical thinking. Competitive student candidates should not only be an order-taker. They should ask hard questions and think about the data problem in the context of the environment that generates the said data. This is related to knowledge of the domains, human contexts, and all kinds of ethical considerations.

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Xingye Qiao Ph.D.: I don't know what you mean by good places. West coast remains to be a hot spot, though there are enough opportunities everywhere, NYC, Boston, DC, to name a few.

How do you envision technology impacting Data Analysts in the next 5 years?

Xingye Qiao Ph.D.: On the Ph.D. level, yes. Greater computing power will move the research activities very rapidly.

Not so much at the undergraduate level. If any change, it is likely not due to technology innovation but an open mind to change our existing curriculum.

Will there be an enduring impact of the coronavirus pandemic on Data Analysts?

Paul Feit: The risk of long term disruption is financial. If business sectors collapse, as in 2008, it may take five years to recover. But if the majority of companies merely take a financial hit (instead of bankruptcy), life will return to normal very quickly.

The fields related to disease control will probably undergo a hiring boost. This covers both medical science but also statistical analysis. People will debate for years about the significance of different social strategies (like masking).

Are there any particularly good places in the United States for Data Analysts to find work opportunities?

Paul Feit: A bachelor's or minor in Mathematics is sort-of a 'vanilla' degree. It is a boost in many careers; it tells potential employers that the graduate is ready for the quantitative needs in any position. Just about every position has some quantitative need. A minor in Mathematics alerts employers that the candidate brings computational finesse to whatever his/her major.

Jobs for higher degrees are in academic institutions and companies big enough to need analysis of their proprietary data. Computer companies appreciate mathematical credentials, but may expect these to be in addition to a computer science background.

How do you envision technology impacting Data Analysts in the next 5 years?

Paul Feit: Ironically, technology tends to conceal mathematics. Once the solution to a problem becomes an algorithm, it is reduced to a button click.

The impact on the field depends on the application:

• Research. Computing power has enabled mathematicians to look at more examples of a problem than ever before. This change actually began in the 1990s. The goal of theoretical mathematics is to establish firm theorems, but new results often come by inspecting examples for a trend.


• Business. 'Big data' is the buzzword for the exciting opportunity to produce new strategies by analyzing more data than was possible in the past. There is a question mark over this area. Converting the idea into practice has been harder than one might hope. (A historical precedent is Artificial Intelligence. That idea seemed within grasp in the 1950s, but it has defied repeated attacks.)


• Warning: The following may sound snide. It is not meant to be. Many companies still rely on old software for certain computations. Much of the technical software was programmed before computing power made it truly useable (that is, it could not actually crack the relevant problem in real-time). Some of these drafts are rife with mistakes. Updating is a double challenge: you need a good programmer AND someone with sufficient understanding of theory to spot and correct mistakes.