What Tasks Do Data Science Professionals Do?
- Analyze, manipulate, or process large sets of business or financial data using statistical
- Apply feature selection algorithms to models, predicting outcomes of interest such as sales, attrition, and healthcare use.
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained
- Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
- Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
- Design surveys, opinion polls, or other instruments to collect data.
- Identify business problems or management objectives that can be addressed through data analysis.
- Identify relationships and trends or any factors that could affect the results of research.
- Identify solutions to business problems, such as budgeting, staffing, and marketing
decisions, using the results of data analysis.
- Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.
- Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
- Recommend data-driven solutions to key stakeholders.
- Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
- Write new functions or applications in programming languages to conduct analyses.
Where Do Data Scientists Work?
According to the US Bureau of Labor Statistics, data scientists held about 113,300 jobs in 2021. The largest employers of data scientists were:
computer systems design and related services
management of companies and enterprises
insurance carriers and related activities
management, scientific, and technical consulting services
scientific research and development services
How Much Do Data Scientists Earn?
Data science professionals are rewarded for their highly technical skill set with
competitive salaries and great job opportunities at big and small companies in most
industries. Data science professionals with the appropriate experience and education
can make their mark in some of the world's most forward-thinking companies.
The median annual wage for data scientists was $100,910 in May 2021, according to
the US Bureau of Labor Statistics. Employment of data scientists is projected to grow 36 percent from 2021 to 2031,
much faster than the average for all occupations. About 13,500 openings for data scientists
are projected each year, on average, over the decade.
Further, Glassdoor.com estimates the average base salary for data scientists is $104,014. The employment website predicts a 28 percent increase in demand for data scientists
by 2026, to fill 5,971 job openings. Glassdoor rates data scientist as the No. 3 Best
Job in America (2022); and data scientist has been placed as a top three best job
every year since 2016.
More computing salaries and data sources.
What Skills and Qualifications Do Data Scientists Need?
Data science professionals are well-rounded, data-driven individuals with high-level technical skills. They are capable of building complex quantitative algorithms to organize and synthesize
large amounts of information to answer questions and drive strategy in their organization.
At the crossroads of several disciplines, data science positions require programming
skills, mathematical and/or statistical knowledge, and business domain expertise.
Data scientists need to be curious and result-oriented with exceptional industry-specific knowledge and communication skills for explaining
highly technical results. Because data science involves the use of algorithms and
statistical techniques, students need extensive study in mathematics and statistics. High school students interested in becoming data scientists should take classes
in subjects such as linear algebra, calculus, and probability and statistics.
At the college level, courses in computer science are important in addition to math
and statistics. Students must learn data-oriented programming languages as well as
statistical, database, and other software for presenting analyses. Data scientists
typically need at least a bachelor's degree, but some jobs require a master's or doctoral
degree. Common fields of degrees earned by data scientists include mathematics, statistics,
computer science, business, and engineering.
Gaining specialized skills within the data science field can distinguish data scientists
even further. For example, machine learning experts use high-level programming skills
to create algorithms that continuously gather data and automatically adjust their
function to be more effective.
The following skills are required for most jobs within the data science field. The
extent to which particular skills are used on a day-to-day basis depends upon the
- Data management: Collecting, organizing, cleaning, and manipulating data.
- Coding: Using a variety of languages such as SQL, Python, or R; sometimes also Java, C++,
- Programming: Writing computer programs and analyzing large data sets to uncover answers to complex
- Data visualization: Using BI tools such as Tableau, Power BI, Looker, etc.
- Database modeling: Understanding how databases work.
- Statistical analysis: Applying data analysis to gain insights, identifying patterns in data, and developing
a keen sense of pattern detection and anomaly detection.
- Mathematical knowledge: Applying mathematical knowledge to data analysis to calculate metrics.
- Machine learning: Implementing algorithms and statistical models to enable a computer to automatically
learn from data.
- Computer science: Applying the principles of artificial intelligence, database systems, human/computer
interaction, numerical analysis, and software engineering.
- Data storytelling: Communicating actionable insights using data, often for a nontechnical audience.
Data scientists also need soft skills, including:
- Business intuition
- Analytical thinking
- Critical thinking
The Future of Data Science
Innovations in the methods for analyzing, visualizing, and interpreting data, and
collaborating around data with diverse stakeholders, have become key to data-intensive
discovery in nearly every field. As a result, data science is rapidly becoming a new
paradigm for research and discovery, integrating approaches from computer science,
statistics, applied mathematics, visualization and communication, and many application
The need for data scientists shows no sign of slowing down in the coming years. Employment
growth for data scientists is expected to stem from an increased demand for data-driven
decisions. The volume of data available and the potential uses for that data will
increase over the previous decade. As a result, organizations will likely need more
data scientists to mine and analyze the large amounts of information and data collected.
Data scientists' analyses will help organizations make informed decisions and improve their business processes, design and develop new products, and better
market their products.
Data Science at Michigan Tech
The Michigan Tech Data Science B.S. program delivers a broad-based education in data science fundamentals, data mining, predictive
analytics, communication, and ethics. You'll will gain a competitive edge through
a technical focus area in software engineering, cybersecurity, statistics, or business
technology. And you'll have the freedom to explore and develop your own interests
in one or more domains.
At Michigan Tech, business, computer science, mathematical sciences, and computer
engineering are the foundations for our STEM-accredited, interdisciplinary master's
degree in data science. Faculty and courses for the graduate program come from colleges
and departments across the University.
The Master of Science in Data Science provides a comprehensive, course-based education in data mining, predictive analytics,
cloud computing, data science fundamentals, communication, and business acumen. Plus,
you'll gain a competitive edge through domain-specific specialization in disciplines
of science and engineering, giving you the space to explore and develop your own interests
in one or more domains.
The data science master's degree requires successful completion of 30 approved credits:
12 credits of core courses and 6-12 credits of approved domain electives. And while
the degree program is a course-based curriculum, you'll get involved in many hands-on,
real-world activities and projects in these courses. The skills and knowledge you'll
gain are building blocks on your path of lifelong learning in the field of data science.
The 9-credit-hour Michigan Tech Graduate Certificate in Data Science Foundations builds competency in data science techniques including predictive modeling, data
mining, information management, and data analytics.
A graduate certificate can be completed as a stand-alone credential, although you
may be able to stack your certificate coursework toward a master's degree. Similar
to a master's degree, a graduate certificate is more narrowly focused on a specialized
field. A smaller investment in time and money than a master's, the Michigan Tech Graduate
Certificate in Data Science Foundations entails completion of one required course
and two of three allowed electives.
Current Michigan Tech undergraduate students can fast-track their careers with the
accelerated master's degree in data science (BS-MS, BA-MS) program. The accelerated
program provides a pathway to earn both a bachelor's and master's in data science
in just five years of full-time study.
The accelerated master's in data science program is open to all high-achieving undergraduate students at Michigan Tech. Students
may double count up to six courses toward both the bachelor's and the master's degree.
Students with an overall GPA of 3.0 or higher can apply for admission to the accelerated
MS in Data Science program any time upon attaining junior class standing, but must
apply prior to being awarded their bachelor's degree.
Data Science at Michigan Tech
Only at Michigan Tech
Michigan Tech graduates are in high demand. The University hosts two Career Fairs
annually, each attracting hundreds of employers from multiple industry sectors, all
hiring for internships, co-ops, and permanent positions. As many as 7,000 student
interviews are available to students during each Career Fair. The semi-annual Career
Fair is preceded by CareerFEST, a series of casual networking events and career development
workshops to help students prepare.
Michigan Tech faculty and students are engaged in cutting-edge data science research.
And while the data science master's degree program is course-based, students have
many opportunities for graduate and lab assistantships, internships, and other real-world
activities and projects.
The College of Computing
Founded in 2019, the College of Computing is one of the first colleges in the nation—and
the only college in Michigan—to focus solely on computing. Digital transformation
has morphed every discipline into a computing discipline, and industries like manufacturing,
criminal justice, marketing, and healthcare are all being reinvented by digital technologies.
The College of Computing is making sure that today's and tomorrow's employers have
the computing talent they need to thrive in this brave new world.