What's the Average Entry Level Data Analyst Salary?

At a time where hiring business trends point to a preference for experienced candidates, entry-level data analysts are one professional which defies the norm. 

To contextualize, let’s look at the stats. 

To begin with, it’s commonplace for recruiters to value previous years of experience in a given professional when sifting through candidates. 

According to stats shared by NACE Job Outlook, on a scale of 0 to 5, the need for previous work experience had a score of 3.7 when it came to the influence it had over recruiters when hiring. 

Yet, with data analysts, it is also not uncommon to see entry-level positions being advertised on the web in large numbers.

After all, despite the lack of formal work experience seen in an entry-level candidate, the reality is that usually, they will have already sharpened the skills needed to accomplish their role in their academic training. 

That said, while the need for these professionals is undisputed, there is, however, one matter that is: What’s the average entry-level data analyst salary? How much less is it than that of a seasoned data analyst? 

We’re going to be answering questions like these and many more in this blog post.

Step into the world of entry-level data analyst jobs to learn not only what their day-to-day activities look like, but also how factors such as their responsibilities and location play a huge role in determining what their cash salaries pan out to be.

Let’s get right into it. 

Junior Data Analyst Average Salary

Credits: PayScale

Based on published by PayScale, the average junior data analyst’s base salary stands at $49,084. 

The stats provided also indicate that for companies that practice profit-sharing, entry-level analysts tend to rack in an average of $1,000.

On the salary range spectrum, entry data analysts rack in as low as $38K annually while they can secure as much as $68K a year. 

Naturally, there are factors that affect which end of the stick an entry-level data analyst gets.

How Location Affects An Entry Data Analyst Salary

Location is one of the biggest factors in determining salary expectations for entry-level data analysts.

Credits: PayScale

For example, in California, the average salary for an entry-level data analyst position exceeds the national mean by $22%.

Compare that to a drop by as much as 10% as is recorded in Illinois. 

Therefore, it’s fairly obvious that while an entry-level data analyst can pull in a solid annual salary, the difference between what you can expect to pull in if you live in California vs in Illinois might be a deciding factor in where you decide to settle down. 

Entry Data Analyst Salary Key Takeaways

All in all, when it comes to salaries for entry data analysts, there is no hard, steadfast rule. 

A major influencer in determining how much you can expect to get paid depends heavily on where you are located. 

Be sure to leverage platforms such as Glassdoor and Google to find out how much a data analyst makes. 

Keep your eyes peeled for full-time job openings.

That said, it all boils down to you and what you believe you're worth.

If you can demonstrate that you have a curriculum vitae that exceeds that of the average entry data analyst, be it in experience level or more, then by all means you should be aiming for more than what they pull in.

At the end of the day, you should never settle for less when you know that you deserve higher pay.

FAQ

What Does An Entry Level Data Analyst Do?

An entry-level data analyst is someone who, despite having minimal professional work experience in data analytics, carries out the task of organizing and breaking down complex company data with the end goal of presenting the resulting analysis in an understandable format for the relevant parties. 

In other words, an entry-level data analyst has to bear the weight of sifting through data compiled by the company, make inferences or conclusions, and, in turn, relay those inferences and conclusions to those who need them. This may be anyone from the company’s board of directors, executives, and managers to its stakeholders and investors.

Considering that this is an entry-level position, a company assumes added responsibility by contributing to your training either through workshops and seminars or investing more in orientation material to help ease you into the position for which you have been hired.

The reasons are obvious. Unlike a senior data analyst, their junior counterpart doesn’t have the experience or familiarity with working in a company to seamlessly transition into your work culture and even the demands of your business in one go.

Similar to senior data analysts, an entry-level data analyst can make use of one of four data analysis processes to achieve the results demanded by the company. 

In no particular order, these processes are: 

• Prescriptive Analytics: Through predictive analytics, the data analyst leverages existing company data in order to offer actionable insight by way of a solution that can be applied to a problem.
• Descriptive Analytics: As the name implies, descriptive analytics centers around describing the events and agents which provoked a particular occurrence. 
• Predictive Analytics: In predictive analytics, a junior data analyst leverages patterns and trends that crop up from data analysis to make inferences about how company data may present itself in the future. 
• Diagnostic Analytics: Here, the only thing that a data analyst is concerned about is understanding what were the underlying elements which led to the occurrence of a particular phenomenon.

Having said that, needless to say, the processes used by a data analyst may lead one to confuse them with similar profiles such as business analysts and data scientists.

However, make no mistake: they are not one and the same.

A business analyst (also known as a financial analyst, business intelligence analyst, assumes the responsibility of delivering advice to a business or company that will help in their strategic decision-making. To do so, they examine the data analysis provided by a data analyst.

In a similar vein, an expert in data science (more commonly called a data scientist or data engineer) is someone who goes through data in order to detect areas where a business can improve. 

Unlike the previous two profiles, a data analyst’s role does not involve strategic decision making.

What Responsibilities Does A Junior Data Analyst Assume?

Let’s start off by saying the obvious: it is impossible to name every single responsibility that a junior data analyst has to assume, just like it is equally as impossible to say that all junior data analysts carry out the same responsibilities.

Each data analyst has their own set of tasks that differ in accordance with the business model of the company as well as its specific data analysis needs.

To put things into perspective, it would be incredulous to assume that a data analyst applying predictive analytics in a football agency will carry out the same responsibilities as one applying diagnostic analytics for a Fortune 500 company. 

However, with all things in life, there are some general similarities shared among junior data analytics.

These include: 

• Creating reports: Of course, an entry-level data analyst must generate reports that document their work. That’s a no-brainer. After all, what purpose does it serve to strip apart complex company data if you don’t keep track of what you’ve done? To be more concrete, however, the most taxing aspect of this responsibility is that the entry-level data analyst must simplify their research and make it understandable to a layperson by way of data visualization. This is easier said than done. Usually, an expert in a field may assume that another person is familiar with the language of their field, but that isn’t always the case. For that reason, particular emphasis must be placed on the need to dumb down the complexities of all reports that are issued. 
• Recognize patterns in data analysis: What’s more, entry-level data analysts must be adept in spotting trends and tendencies within a batch of data that will help to inform the conclusions that are drawn from their analysis. Naturally, the degree to which pattern recognition will play a role in their day-to-day tasks will depend on the type of data analysis process that they apply. 
• Store and access data: A junior data analyst ought to be able to secure and retrieve data in a seamless and painless fashion. This is the most technically demanding skill that is expected from an analyst. For this, they must leverage software tools and programs such as Microsoft Excel, Machine Learning applications, SQL and Python tools, and some type of database.

What Requirements Are Needed To Become An Entry Data Analyst?

Junior level data analysts are lucky enough to enjoy entry into their career path from a diverse background.

For starters, due to the obvious lack of work experience, emphasis is placed on a junior data analyst’s academic training and skill set. 

For that reason, a candidate with a Master’s degree in Statistical Analysis, Big Data, Mathematics, Computer Science, or a similar field are all highly valued.

That said, candidates who have a Bachelor’s degree or some type of specialized training in research are also sought after by companies.