Careers in data science are some of the most sought-after in the world and that trend shows no signs of stopping. With the widespread use of AI, IoT devices, and streaming and real-time communication services, it’s no surprise many people are pursuing careers in data. In fact, data scientist is the second best job in America, according to Glassdoor.This extraordinary progress in data science has created extraordinary demand for data professionals across many industries. This is great news for aspiring data scientists because it means rewarding salaries and benefits. Increased demand paired with a shortage of trained applicants means hundreds of thousands of new data science job opportunities.Even if you’re only just discovering data science and the possibilities of a career as a data professional, there’s never been a better time to start, and ample opportunities await you that never existed before.
What Does a Career in Data Entail?
Careers in data, simply put, revolve around the collection, cleaning, organization, manipulation, visualization, and interpretation of data. Even though different career paths specialize in different areas, and each path requires some specific processes and tools, many paths share some common themes.
From budget analysts who inform the government where to spend tax dollars to data engineers who help users like you and me stream our favorite movies, the data science universe is vast and ever-expanding.
As a result, there are hundreds of job titles in the data world, and many overlap regarding the skills they need. This gives the data professional a uniquely flexible position to develop useful skills while they discover which specialization is right for them.
A few job titles in data include the following:
- Data analyst
- Finance analyst
- Operations analyst
- Healthcare analyst
- Marketing analyst
- Data scientist
- Data engineer
- Data technician
- Business intelligence analyst
- Data mining engineer
- Database administrator
- Data and analytics manager
- Digital marketing manager
- Transportation logician
- Systems analyst
- Quantitative analyst
- Data architect
- Software developer
- Computer network architect
- Database administrator
- Information security analyst
If you’re wondering where to acquire some of these jobs, Dataquest created a fantastic resource on how and where to find data jobs - link here.
How to Become a Data Professional in 2021 and Beyond
In the past, the only way to get a decent job in data would’ve been to show up with a bachelor’s degree in computer science, mathematics, statistics, or some related field. But with the growing demand for data professionals and low supply of trained applicants, hiring managers are now placing more value on skills and relevant experience than formal education.
There’s now an opportunity like never before for new applicants in data science to acquire a highly rewarding, entry-level job without a college degree, assuming the applicant can demonstrate aptitude in the necessary skills and a desire to learn and develop their career in data.
A study by Glassdoor lists a number of companies no longer requiring degrees for many open data science positions. A few of these companies include Google, Apple, Nordstrom, Publix, Starbucks, IBM, Bank of America, and more. It’s becoming increasingly common that businesses are hiring based on ability, not degrees.
So, how do you get started on the data science career path? Here’s our best advice:
- Research the field, and discover your role. If data science seems right for you, develop a learning plan to guide your career studies!
- Join the data science community on platforms like Kaggle and GitHub for ideas and support. If you can, find a mentor!
- Develop fundamental data science skills through online courses and bootcamps; consider certifications instead of degrees. We suggest learning with Dataquest courses if you prefer to learn by writing code, not by watching videos.
- Leverage these skills to build a portfolio of real work to showcase your abilities.
- Apply for an internship or your first entry-level job to demonstrate your abilities.
- Never stop learning; pursue further education in data science, and hone your skills.
Essential Skills, Tools, and Technology for Careers in Data
A carpenter is only as good as his tools. Likewise, a data professional depends not only on their skills but also on an array of powerful tools and cutting-edge technologies.
Below is an overview of the resources and skills you’ll use as a data professional:
Proficiency in these areas is non-negotiable for many data professional roles. Luckily, there are incredible resources already available to begin developing the necessary skills for a career in data. Dozens of companies are now offering online data professional bootcamps, online courses, or certifications that can be as general or as specialized as you like.For example, Dataquest offers specific career paths designed to be the only resource you need to take you from beginner to job-ready.
For example, Dataquest offers specific career paths designed to be the only resource you need to take you from beginner to job-ready.
You can also choose to take a more specialized approach with our skill paths, like Machine Learning Intro with Python, Probability and Statistics with Python, R Basics for Data Analysis, and many others.
Data Jobs Growth and Outlook
Demand for data professionals has never been higher, and by all accounts, they are some of the fastest-growing career opportunities. The World Economic Forum’s Jobs Report 2020 found that data analysts, machine learning specialists, and big data specialists are the three fastest-growing jobs across industries in the United States.
Every year, LinkedIn releases their Emerging Job Report, outlining the hottest new jobs based on data they collect from their popular job board. In 2020, data science-related jobs occupied three out of the top ten emerging jobs:
- #1: AI specialist roles grew annually by 74% in the past four years.
- #3: Data scientist roles grew 37% in the past four years.
- #8: Data engineer roles grew 33% in the past four years.
Additionally, Interview Query Blog analyzed over 10,000 data science-related interview experiences and discovered that data science positions are still growing extremely fast, despite a slight slowdown during the pandemic:With such an explosion of demand comes higher salaries — even entry-level data professionals can demand respectable numbers and benefits. reports that careers in data visualization tout an average salary of $85,000. Data analysts, on the other hand, working in the finance, insurance, scientific, or technical services, can command a salary of $90,000, according to a study by Springboard. Data scientists, according to , average a median salary of $96,455 per year, while the sets the average at just over $100,000. Specialized, senior, or manager data science positions can expect salaries of upwards of $200,000.
However, the reduction in growth rate was not demonstrated with FAANG companies—they saw a 25% increase in interviews compared to last year.
According to the latest data from the Bureau of Labor Statistics, by 2030, the data science job market is set to increase by nearly 33%, more than three times the national average. Additionally, the big data market size is projected to grow by more than $100 billion.Glassdoor PayscaleBureau of Labor Statistics
Are you ready to join the boom of rising talent in data science? Well, you can! But gaining the skills you need won't happen overnight. If you build healthy learning habits and maintain a frequent learning routine, within six months to a year, you could begin an incredibly rewarding and life-long career as a data professional. If that sounds good to you, all of us here at Dataquest are ready to help you get started.
Stop waiting, jumpstart your data science career today
With Dataquest, you can acquire the necessary skills and knowledge for in-demand and highly rewarding data science positions. If you want to increase your salary and job opportunities, we have the tools and resources you need.