The role of a data analyst can be very tricky to define but let’s take a look at the average pay for a data analyst job. It’s a profession that is still evolving, being shaped and molded by the companies that employ them and the individuals who fill that role. Some company’s data analyst job openings demand their analysts have advanced degrees and years of experience, while others are happy if the person they hire can work a spreadsheet. It all comes down to a company wanting to have actionable insights to work with in order to make better business decisions.
The salary for a data analyst job depends a lot on where you live. According to Salary.com, a data analyst in California earns an average high of $96,637 a year, while data analysts in Florida take home a high of $82,189 a year. A lot also depends on the years of hands-on working experience.
What is the future outlook?
According to the Bureau of Labor Statistics, data analysts are growing by 25% over the next ten years. The reason for the increase in data analysts is due to the growth in data collection by companies, so there is a need for people who have the skills to analyze the data. In fact, everything that a business does relies on an analyst to convert numbers into usable information.
What do data analysts do?
Lots of people can tell you that data analysts analyze data, but the reality of the data analyst’s job is a lot more complicated than that. Data analysts crunch data for companies, governments, and other organizations to help their organizations make better decisions. These analysts are the ones collecting, analyzing, and interpreting the data that helps organizations make strategic decisions. They use a variety of data science tools and techniques to ensure that the data they are analyzing is accurate and relevant.
What technical skills are needed?
- Statistics and business intelligence tools
- Excel – spreadsheet and reports knowledge
- R and Python programming languages
- SQL (Structured Query Language)
- Use of Data Visualization tools
What functional skills are needed?
- Critical thinking – look at concepts, judge them against what you already know to make decisions about findings
- Presentation skills – present data findings in a manner others can understand
- Problem-solving – solve problems quickly and make sound decisions
- Attention to detail – spot and resolve errors
- Research skills – gather information and data from diverse sources
- Business and domain knowledge helpful – understanding of what the data represents and patterns in the industry to understand the needs of the market
- Communication – communicate their findings to the rest of the company
Average pay for a Data Analyst Job Based on Experience
Earning potential and total compensation will be based on the kind of work you do, how many years of experience you have, and what type of company you are working for. Analyst jobs are in demand and the average salary depends on a variety of factors that all influence the size of your paycheck, but the main factor is how much your company values your work based on their need.
Now, let’s look at the salary for a data analyst job. Below you can see the average annual salary (base) for a typical data analyst role from an entry-level junior data analyst that can earn up to $56,000 to a more senior analyst that can go earn an average of $73,000.
The average data analyst salary for the selected areas below will give you an idea of the salary range to expect. Keep in mind depending on industry, location, and need can cause these salaries to fluctuate.
What you can do to increase your annual salary as a data analyst?
There are certain skills, degrees, and certifications that are slightly above that of a typical data analyst that can really help you boost your marketability when seeking job opportunities. Based on skills some job postings may also have a job title like Business Intelligence Analyst, Big Data Analyst, Senior Data Analyst, or Senior Business Analyst.
Skills that will make you stand out:
According to Payscale.com, having experience with JMP Statistical Software can have a 54% impact on your base salary. If you have a strong database architecture background can increase your with by a huge 47%.
Knowing Natural Language Processing (NLP) can get you 35% more. Having experience with the business intelligence software Looker (which is now part of Google Cloud) can boost your salary by 35%. For healthcare industry-related organizations, having a bioinformatics background can get you a 29% increase.
The ability to work with the data warehouse product Amazon Redshift can get you an additional 28%. If you know Oracle’s procedural language PL/SQL, you can increase your value by 26%. Being able to use the open-source unified analytics engine Apache Spark can raise your salary by as much as 24%. The ability to manage a team will give you a gain of 24%.
Finally, experience with cloud analytics products like Teradata can raise your salary by as much as 23%.
Common degrees to provide a solid foundation:
- Computer Science (best if leaning toward a technical career path)
- Economics (best if leaning toward the business side career path)
- Mathematics (best if leaning toward data scientist career path)
- Statistics (best if leaning toward data scientist career path)
- Finance (best if leaning toward the business side career path)
Certifications that can impact your marketability:
- Certified Analytics Professional
- Tableau Certification
- AWS Certified Data Analytics – Specialty
- SAS® Visual Statistics Credentials
- CCA Data Analyst by Cloudera
- Microsoft MCSE – Data Management and Analytics
- Microsoft Certified Data Analyst Associate
Career path for a data analyst
There are 3 easy ways to break down the career path for a data analyst role. Payscale.com did a great job of showing this. Keep in mind these are average overall not per city. Some areas may fluctuate depending on demand, industry, and cost of living.
The first is taking the path of moving toward being a senior data analyst which has an average base salary of $96K and from there most move on to be a data scientist which ranges from mid $117,692 to a high $145,582, stay on the data analyst track, or become an analytics manager from mid $97k to a high of $128K.
The second path is to go down the data scientist route. This is where the mathematics and statistics degrees really come into play. The data scientist salary has a midpoint of $96 to a high of $135K then you can then move into similar roles. One is a senior data scientist which pays a median salary of $127 to $161K on the high end, another is a data science manager which will be mid $136K to a high $181K, or a data science director with a midpoint of $157k to $205K on the high end.
The third option is to become an analytics manager on the business side of an organization and pays typically $97K to a high of $128K. The areas to consider from an analytics manager is to look at being a director of analytics with a salary estimate of $129k to a high $175K, a senior manager of business analytics with an average salary of $124K to a high $164K and a business insight and analytics manager that pays a mid of $100k to a high of $134K.
Locations with the highest-paid data analysts
Another factor that impacts compensation in a data analyst role is the location. The highest paying locations currently are San Francisco, London, and New York; however, they also have a high cost of living.
Industries paying the highest salary for data analysts
After taking a look at the openings and the salary ranges on Glassdoor.com and other job sites, it seems the most needs are coming from specific industries. The top 4 listed.
- Information Technology/Technical Services
The data analyst is a crucial link between IT, business, and the users they serve. As a data professional, you have many options to steer your career and be involved in different areas of a company and continue to grow and learn.
With the demand for data analysts projected to grow by 25% over the next decade, the importance of continuous learning and specialization in areas like statistical software, database architecture, and Natural Language Processing to enhance marketability and salary prospects. Additionally, explore career paths for data analysts, indicating a promising outlook for those in the field.