A quick search on LinkedIn reveals more than 312,000 data scientist jobs nationwide. More than 220,000 of these jobs were posted in the last month. More than 19,000 were posted in the last 24 hours alone, suggesting that those who pursue a data science degree can literally (and figuratively) bank on job security.
Data scientists in demand
Data scientists work in virtually every industry, including healthcare, computer science, information technology, retail, marketing, manufacturing, transportation, communication, education, insurance, finance, science, security, government, nonprofit, and law enforcement just to name a few. Companies such as Facebook, Amazon, IBM, Kayak, Capital One, The New York Times, and others continue to clamor for those with data science training who can drive business intelligence using voluminous and complex data.
What exactly are these and other companies looking for? Following are just a few snippets taken verbatim from data science job openings posted recently on LinkedIn:
- Use big data tools (e.g., Hadoop, Spark, H2O, and AWS) to conduct the analysis of billions of customer transaction records.
- Establish scalable, efficient, and automated processes for large-scale data analyses that will tie into production systems.
- Use predictive analytics and machine learning to create new products or drive business decisions.
- Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products.
- Interpret, document, and present/communicate analytical results to multiple business disciplines, providing conclusions and recommendations based on customer-centric data.
Finding the right data scientist training
Employers want to hire data scientists who don’t just know the technology but who know what to do with it; agile communicators who are well-rounded can remain flexible as new challenges and business needs arise. If you’ve thought about pursuing a career in data science, look for a program that provides not only a solid foundation rooted in statistics and computer programming but also one with instruction in economics, business management and communication.
Aligning your education with the top 12 most in-demand data science skills
The interdisciplinary nature of the University of Wisconsin Data Science program caters directly to the types of skills that employers seek. Many employers require a master’s degree in data science or a comparable discipline (e.g., statistics, computer science, or mathematics) as well as the ability to perform these 12 most-common tasks:
- Create and manage simple databases in Access and SQL Server.
- Write and execute SQL statements to retrieve and manage data.
- Analyze data to solve basic analytics problems using Excel and R.
You’ll learn all of this and more, including how to use other well-known data science tools (e.g., PowerBI and Access) in the course, Foundations of Data Science.
- Use Python and R to analyze real-world data.
- Use an application programming interface (API) to collect real-world data from social media.
- Clean and format data for analysis.
You’ll learn all of this and more in the course, Programming for Data Science.
- Use tools and software such as Hadoop, Pig, Hive, and Python to compare large data-processing tasks using cloud-computing services.
You’ll learn this and more about big data analysis in the course, Big Data: High-Performance Computing.
- Help non-technical professionals visualize, explore, and act on data science findings.
You’ll master technical, informational, and persuasive communication in the course, Communicating about Data.
- Create effective visuals to maximize readability, comprehension, and understanding of complex datasets.
You’ll learn this and more in the course, Visualization and Unstructured Data Analysis.
- Use data and predictive analytics to inform the decision-making process.
You’ll learn this and more, including optimization, decision analysis, game theory, and simulation in the course, Prescriptive Analytics.
- Transform findings from data resources into actionable business strategies.
- Explain how data assets can be used to develop competitive advantage.
You’ll learn this and more about how to obtain decision-making value from an organization’s data assets in the course, Data Science and Strategic Decision Making.
In addition, the University of Wisconsin partners with an industry advisory board dedicated to helping students bridge the gap between classroom learning and real-life data science challenges. Their continual input helps ensure course content meets today’s employer needs in this rapidly evolving field. This makes for a smooth transition into the workforce.
Giving employers what they need and want
Upon completion of the University of Wisconsin master’s in data science program, individuals are prepared to:
- Identify organizational questions for which data science can provide answers.
- Collect and manage data to devise solutions.
- Select, apply, and evaluate models to solve data science tasks.
- Interpret data science analysis outcomes.
- Effectively communicate data science-related information in various formats and for various audiences.
- Value and safeguard the ethical use of data.
- Transform findings from data resources into actionable business strategies.
Increase your value to employers seeking savvy, well-rounded data scientists by earning a University of Wisconsin master’s degree in data science. To learn more, download a program guide at https://datasciencedegree.wisconsin.edu/.
