Quick Highlights:
- Data science jobs are projected to grow by 35.2% between 2022 and 2032, making it a lucrative and in-demand career.
- Data scientists earn substantial salaries, with median wages around $103,500 per year and potential earnings between $132,000 and $190,000.
- Key skills for data scientists include programming (especially Python), data manipulation, data visualization, and a strong foundation in math and statistics.
- Data science offers career versatility across various industries, including tech, healthcare, and business, allowing professionals to work on diverse and impactful projects.
What is data science? At its heart, data science revolves around data analysis, programming, and data mining. As a rapidly expanding field, data science jobs are expected to grow by 35.2% between 2022 and 2032, according to US News.
Whether you are interested in data engineering or machine learning, a data science career is a financially rewarding decision. Depending on the program you choose, you may be able to learn data science online or in a traditional classroom setting. While the decision to learn data science can be expensive, it is typically worth the investment. Once hired, a data scientist earns a total salary between $132,000 and $190,000, according to Glassdoor.
What Is Data Science?
Data science is the study of data and how to extract important information from data. It is a blend of specialized programming, data science math, analytics, statistics, machine learning, and artificial intelligence. Because there are so many data sources that need to be analyzed, there are many job opportunities in this industry. In fact, data science was recently labeled by Harvard Business Review as the “sexiest job of the 21st century.”
Organizations need data scientists to interpret data. With this information, they can make decisions and do strategic planning. Someone who has a data science career may perform different tasks based on which stage they are working on within the data science life cycle.
- Creation and Ingestion: At this stage in the data science life cycle, data is new and hasn’t been processed yet. Customer information, pictures, and log files are absorbed through web scraping, manual entry, and data streaming.
- Storage and Processing: Next, the data is stored and processed into a usable form. A data scientist manages the way data is stored and develops a workflow for analytics. They may use tools from deep learning and machine learning. Before storage, they will clean up the data and remove duplicates.
- Analysis: Data analysis is the next part of the data life cycle. Results from A/B testing and other modeling efforts help organizations get important insights for business decisions.
- Communication: At this point in the life cycle, data scientists turn insights into actionable reports. They may create visualizations so that stakeholders can easily understand the data. Depending on the position, they may use Python for data science, R, or other programming languages to create these visualizations.
The Basic Foundations of Data Science
Once you decide to learn data science online, there are a few subjects you will need to take. To succeed in this field, you will need to study data science math, programming, data manipulation, and data visualization. After you have mastered the foundations of data science, you can take advanced courses. For example, you may study data exploration, processing, machine learning, convolutional neural networks, deep learning, and big data technologies.
Data Science Math
Before you can learn data science and advanced programming, you must master several mathematics courses. In general, you will need to take linear algebra, calculus, probability, and statistics. Math classes are typically prerequisites for data engineering and programming courses, so it’s important to sign up for these classes early on in your academic career.
Data Manipulation
If you want to start a data science career, you need to understand data manipulation. This means you must learn Python and R. In particular, you will need to familiarize yourself with Numpy, Pandas, and Dplyr.
Data Visualization
Other aspects of Python for data science are also important to learn. To excel at data visualization, you must familiarize yourself with Matplotlib and Seaborn. Additionally, you should understand R’s ggplot2 if you want to create graphics for data visualization.
Programming
To learn data science online, you must understand computer programming. Python is the predominant language for data visualization. As a part of your studies, you should familiarize yourself with control structures, functions, syntax, data structures, object-oriented programming, and basic Python concepts.
How to Learn Data Science for Beginners
Like many tech jobs, data science is all about what you know. While there are four-year degrees in data science and analytics, you can learn data science and get hired without pursuing a college degree. You can also use a boot camp program to quickly develop your skills and get a job.
If you do want to attend a university, you should start by looking for a college program that specializes in data science. Sometimes, people become data scientists after pursuing degrees in statistics, engineering, computer science, or mathematics. No matter what course of study you pursue, you should take as many math and programming courses as possible. Python is the major programming language used in a data science career, so you should focus specifically on this programming language.
What Is a Data Scientist’s Salary?
According to the Bureau of Labor Statistics, the typical data scientist earns a median wage of $103,500 per year. This works out to $49.76 per hour. The top 25% of earners brought in more than $136,600 each year.
Specific data scientist roles may pay more or less. While a data analyst earns an average wage of $70,676 per year, a statistician brings in $86,960 annually. Meanwhile, a machine learning engineer garners a whopping $150,186 every year.
Data Science Trends
After learning the answer to, “What is data science?”, the next step is figuring out if a data science career is right for you. If you decide to enter this career field, you won’t have to worry about finding a job. Within this growing career field, you will find 17,700 openings for data scientists each year.
From 2022 to 2032, the Bureau of Labor Statistics expects this field will grow by 35%. In comparison, all occupations in the United States are forecasted to increase by just 3%. If a 35% increase does occur, it means that there will be an additional 59,400 jobs in this field by 2032.
What Does a Data Scientist Do?
The day-to-day life of a data scientist depends on their role in an organization. While some data scientists are responsible for collecting and storing data, other data scientists are in charge of analyzing the data. Depending on the specific job description, a data scientist may take part in some of the following activities.
- Collecting, cleaning, and categorizing data
- Making recommendations to business stakeholders using the data
- Developing and testing different algorithms
- Deciding which data is important for the project
- Communicating results to stakeholders
In the tech industry, data scientists build a data foundation so that they can perform analytics. They use machine learning and other data products to make strategic business decisions. Outside of the tech industry, data scientists are implementing the same techniques in different industries and achieving impressive results. For example, data science has shaken up cancer research and the trucking industry.
Why You Should Become a Data Scientist
If you want a lucrative career with plentiful job openings, you may want to learn data science. At the University of Notre Dame, 100% of data science students are employed six months after graduation. Because there is a low supply of workers in this career field, you will face less competition when you apply for a job in the industry.
Financial Benefits
It is also hard to ignore the financial benefits associated with working as a data scientist. Whether you decide to pursue data engineering or data analysis, a career in data science typically brings a six-figure salary with it. Even in the first year of your career, you will earn an average salary of $104,561, according to Indeed.
Career Versatility
Other than enjoying excellent career growth, you can also enjoy spending your career working with big brands. You don’t have to be limited to just working in the tech industry. If you care about curing cancer or saving the environment, you can easily help a cause with your data science skills. Because data science is required in nearly every industry, this field offers a lot of versatility.
Inexpensive, Flexible Training
As a side benefit, you can pursue a degree or certification in data science from your home. While there are data science degrees at Ivy League schools, you can also find online degree programs and certifications. You can even learn data science free of charge if you go to the right sites.
Skills Needed to Become a Data Scientist
To succeed in a data science career, you will need to master a specific set of skills. Because so much of programming, statistics, data engineering, analytics, and other data science courses are based on math, you should spend extra time and energy on your math skills. Typically, successful data scientists have the following abilities and traits.
- Deep learning
- Data wrangling
- Communication
- Critical thinking
- Statistics
- Curiosity
- Big data
- Data intuition
- Business savvy
- Teamwork
- Problem-solving
- Analytical mindset
Discover a New Career as a Data Scientist
As one of the fastest-growing career fields, data science has a thriving job market and a variety of unique opportunities. Beyond choosing between a job in data engineering or analytics, you can select positions with different brands and industries. For example, you can learn data science to get a job working in cancer research or making better coffee recommendations.
By learning the answer to, “What is data science?”, you can take the first step toward a rewarding career. Once you learn data science, you can access six-figure jobs. Plus, some data science careers only require certifications, so you don’t necessarily have to spend four years studying data science in school.
Sources: