Modern businesses collect and generate huge amounts of data, and they rely on data professionals to help them make sense of it all. Still, not every company needs the multidimensional skills of a Data Scientist. For many smaller companies, a Data Analyst is more than enough. So, if you’re considering getting into the field, now’s a great time to do so.
But, before you sign up for a career in data analytics, you’re probably wondering how much a Data Analyst makes. Below, we’ll explore the average salaries for Data Analysts by location, industry, and experience level. Or, if you’d rather jump right into building the skills you’ll need to excel in this career, check out our Data Analyst Career Path.
Data Analyst salaries based on location and industry
According to ZipRecruiter, the average salary for Data Analysts in the U.S. is $67,294 per year. Still, your salary as a Data Analyst will depend on your location. LinkedIn and Indeed tell us that the average Data Analyst’s salary ranges from $63,000 to $71,053 a year.
To break it down even further, Data Analysts in North Carolina have the lowest average salary at $49,690. Data Analysts in states like New York, New Hampshire, Massachusetts, D.C., and Washington generally earn slightly higher than the given average. Still, in most states, you can expect at least $60,000.
Industries with a higher demand for Data Analysts tend to provide higher salaries. For example, CareerFoundry found that Data Analysts in the mining industry can earn as much as $117,000. Other high-paying industries include information technology, healthcare, finance, insurance, and professional services.
Data Analyst salaries based on experience
Of course, your experience will also influence your salary as a Data Analyst, as well as your responsibilities. Entry-level Data Analysts design business solutions based on the insights they derive from their data and earn about $54,272 on average.
Mid-level Data Analysts with 2 – 4 years of experience earn a slightly higher salary at $70,123 and perform many of the same tasks as their entry-level counterparts. Senior-level Data Analysts with 4 – 6 years of experience take on bigger projects and help train new analysts. Once you get to this point, you can expect a salary of around $87,713.
Lastly, the highest-paid Data Analysts are consultants who work directly with a company’s executives, managers, and clients. These analysts, with 6 years of experience or more, can earn an average of $106,234.
Still, once you launch your career as a Data Analyst, there are several steps you can take to demand a higher income. Indeed recommends building on your technical expertise by learning more programming languages, creating side projects, and transitioning into data science or data management fields.
What do Data Analysts do?
As we explained above, Data Analysts work in a variety of industries. They may be most closely associated with the financial industry because of its heavy reliance on data. There’s also a great demand for Data Analysts in healthcare, marketing, retail, insurance, and technology.
Generally, Data Analysts take large amounts of data in any of these fields and analyze it for trends and patterns — making predictions and finding insights that can better inform a business’s decision-making.
A Data Analyst should be good at handling numbers, details, and managing multiple tasks. You’ll also need to know how to present your findings in a way that your teammates (both technical and non-technical) can understand.
Data analytics itself is changing in instances where big data is involved. Big data refers to any set of data so vast that the standard programs and methods are not adequate to process it or analyze it. If you can show a prospective employer an understanding of the changes happening in the data analytics field, you could land a higher role with more responsibility and compensation.
How to become a Data Analyst
Ready to kick off your career as a Data Analyst and start chasing the salaries listed above? First, you’ll need to learn programming languages like SQL, which is used to query data from relational databases, and R or Python, which are used to organize, analyze, and visualize data. Use any of the courses below to start learning these languages:
Or, if you’d rather build all of the skills you’ll need at once, check out our Data Analyst Career Path. We’ll teach you how to use the languages above, along with libraries and frameworks like pandas and NumPy, to analyze datasets and communicate your findings. Plus, as you complete the Path, you’ll create projects that you can use to build a portfolio, and we’ll even give you some tips on passing your technical interviews once you’re ready to start looking for an entry-level position.