Data scientist is one of the fastest-growing jobs in America. Between 2019 and 2029, employment will grow nearly eight times faster than other occupations, according to the U.S. Bureau of Labor Statistics.
Data scientists work at the intersection of math, computer science, and technology. They process data to derive insights that provide informed structures for decision-making.
Today, every industry has unprecedented access to big data. Yet, many organizations lack the expertise to harness it. No matter your current career or field, you can advance by taking advantage of the burgeoning demand for skilled data scientists.
Use this blog to discover the most sought-after skills for data scientists and how you can learn them.
Data analysis is one of the essential skills for data scientists. It is the process by which data scientists extract insights to solve business problems and uncover opportunities.
Data scientists use various software tools (e.g., SAS, Spark, and more) to analyze, discover, and summarize knowledge pulled from large-scale and complex data. They also employ mathematical and statistical methods, including analytical models, machine learning, and data-mining algorithms.
Another key component of this data science skill set is identifying and solving data issues. To do that, data scientists must know the 4 V’s of Big Data: volume, velocity, variety, and veracity. According to the Information Systems Audit and Control Association (ISACA), understanding these characteristics enables data scientists to “properly review, assess, and audit big data systems and organizational efforts.”
By extracting and articulating new insights, data scientists play a vital role in designing innovative solutions for how we live, work, and interact with the world around us.
Another in-demand skill for data scientists is data visualization. Fortune Business Insights (FBI) forecasted a 10.2% growth rate in the global data visualization market from 2020 to 2027. What’s the driving factor? FBI points to the rising emphasis on information visualization in business and enterprise.
Data visualization is an analysis technique representing data and information through graphics, charts, and maps. It helps data scientists:
- Communicate complex insights to non-technical audiences
- Identify relationships and patterns
- Spot errors and outliers
- Clean and verify data
Data scientists need a variety of skills to produce an effective data visualization. They should first understand the purpose of the visualization. What data is most valuable to the audience and how will it be used for decision-making?
Another important skill is leveraging the various visualization tools. According to a recent survey by Kaggle, the top three tools used by data scientists are Tableau, Microsoft Power BI, and Google Data Studio. Choosing the appropriate visualization is also crucial. Data scientists must depict the data in a format that will meet the end user’s needs.
A firm grasp of these skills enables data scientists to derive the most helpful insights from data.
With rapid adoption worldwide, machine learning has become a sought-after skill for data scientists. Forbes reported that the market is expected to grow by 44% from 2017 to 2024.
Machine learning is a subset of artificial intelligence. It involves computers using data and algorithms to make predictions and classifications without human intervention. For example, data scientists have used machine learning to help health care systems predict hospital readmissions and banks detect fraudulent transactions.
Data scientists should understand the entire life cycle of machine learning—from identifying application objectives and acquiring data to implementing predictive models in organizations.
Python is a must-have skill for data scientists. According to the TIOBE programming index, Python is the second most widely used programming language—and it has the fastest-growing adoption rate. Between August 2020 and August 2021, its popularity rating rose by over 2%.
Python is a general-purpose programming language, which makes it relatively easier to learn and use than other types. It supports numerous data science tools, including machine learning, algorithms, and data visualization.
According to one survey, data scientists in most industries prefer Python over two other popular programming languages, SAS and R. Here are the preference rates for Python by industry:
- Tech/Telecom: 60%
- Other Corporations: 51%
- Consulting: 49%
- Retail/CPG: 44%
- Financial Services: 44%
- Healthcare/Pharma: 40%
- Advertising/Marketing: 37%
Data scientists who are well-versed in Python will thrive in the field now and in the future.
Database management is another fundamental skill for data scientists. Almost every organization stores information in a database, which means data scientists interact with databases regularly.
The data science skill set for database management consists of both theory and design. Data scientists should be familiar with the full scope of tools and technologies needed to create, manage, and analyze large-scale databases.
- The components of a database environment, such as software and procedures
- Tables and data types
- Data manipulation and functions
- Query languages such as SQL
Effective database management also relies on numerous soft skills, including organization, creativity, and an understanding of business needs. These skills allow data scientists to manage big data in logical, innovative, and strategic ways.
Acquire the Skills Required for Data Scientist Roles
Are you seeking career advancement? Apply your experience to the in-demand field of data science.
Worcester Polytechnic Institute (WPI) offers a Master of Science in Data Science Online program that will prepare you to develop and implement data-focused solutions. As a student, you will establish a foundation in data science essentials and personalize your degree path to achieve your career goals.
Graduates of the Master of Science in Data Science Online program have mastery of the following skills:
- Database Management: Extracting and managing data using traditional and cutting-edge methods
- Analysis Techniques: Applying machine learning and data-mining algorithms
- Statistics: Employing statistics and other applied mathematical foundations.
- Data-analysis Software: Using a rich diversity of software tools
- Essential Management and Leadership Techniques: Undertaking a holistic approach to data science, developing interpersonal and storytelling skills alongside technical mastery
WPI’s educational excellence has received recognition from organizations and prestigious publications across the country, including:
- Top 50 Most Innovative Schools (U.S. News & World Report)
- Top 25 STEM Colleges (Forbes)
- #20 Best Value College/Top Return on Investment (Payscale.com)
With WPI’s Master of Science in Data Science online program, you’ll learn how to harness the power of data to advance your career and make a real-world impact.