8 Careers for Data Analytics Grads - Data Science Degree Programs Guide

There is no doubt that data science, and more specifically, data analytics, is a growing field.

In fact, Forbes notes that data analytics is “exploding” and that employment in this field is very strong.

The Bureau of Labor Statistics (BLS) backs this up. For example, it’s expected that jobs in the field of operations research analysis will grow by 25 percent through the end of the decade. Meanwhile, the need for computer and information research scientists is expected to increase by 22 percent by 2030.

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Of course, if you’ve already gotten your degree in data analytics, you likely know that people with your credentials are in demand. The question is, what career path are you going to take?

Fortunately for you, armed with the skills to gather, clean, analyze, and report on data, there are many different directions you can go for employment. What path is right for you? Where will your talents be best utilized?

Below are some top options for graduates with a data analytics degree.

Business Intelligence Developer

As this job’s title may suggest, a business intelligence developer works to make businesses operate more intelligently. They do this by using business intelligence software to analyze large caches of assorted data types. Then, they decipher specific, important, and otherwise hidden bits of information that the business can then use to its benefit.

More specifically, business intelligence developers:

Analyze data at the product and market levels
Use business needs to inform the technical specifications of reporting systems
Make large amounts of data easily accessible for decision-making purposes
Create data-driven reports that help drive and support business decisions
Monitor business performance

Additionally, business intelligence developers maintain platforms that are used for data analysis. They are also often tasked with evaluating existing business intelligence systems and making recommendations for their improvement.

It’s necessary to be very data-savvy for this role, and your education as a data analytics graduate will fit the bill just right.

Fortunately, this is a high-paying job. According to Salary.com, the median annual wage for business intelligence developers is $95,289.

Data Analyst

Probably the most directly applicable job for data analytics graduates is data analyst.

Data analysts work with huge collections of raw data for any number of purposes for their employer companies. In most cases, this data is manipulated and organized in different ways so the analyst can then find answers to specific business strategy questions.

Some companies also package additional responsibilities with the analyst role such as tracking web analytics and analyzing data test methods.

Most commonly, data analysts are responsible for:

Designing databases, maintaining them, and fixing any problems, like coding errors
Mining data and reformatting it in a way that it can be easily digested by others
Interpreting data using statistical tools like descriptive and inferential statistics
Communicating the meaning of data, including patterns and trends in the data, to stakeholders
Using data to make predictions and to inform decision-making

Data analysts carry out these tasks in the context of a team environment. For example, data analysts often work with computer programmers, data engineers, executives, and other stakeholders to improve everything from data collection to data analysis to data storage.

This is a well-paying career with a pay range of $69,819 to $88,715, according to Salary.com. As with any job, though, the salary you can expect to earn depends on a variety of factors, including level of education, level of experience, the company for which you work, and even the geographic location in which you work.

Data Engineer

Data engineers carry out the unique role of performing batch and real-time data processing on company data collections. Data scientists, discussed below, rely on these professionals to make data readable and organized to a basic extent.

Essentially, data engineers develop algorithms that allow them to find trends in data. They are responsible for testing and maintaining these architectures and aligning them effectively with the needs of the business or organization.

This job also entails data acquisition and finding ways to improve the reliability and quality of data that’s collected. Other responsibilities include:

Conducting research
Using statistics, machine learning, and other tools to analyze data
Using programming languages like SQL for data analysis
Developing predictive and prescriptive models
Finding ways to use data to automate processes

Data engineers work as a part of a much larger team, so they must be able to work well with others, support related work, and report on their work to other members of the team.

Data engineering represents a rapidly growing vocation in diverse types of companies today. For example, companies that range from social media giants like Facebook and Twitter to grocery store chains like Kroger to educational institutions like colleges and universities all employ data engineers.

As a data engineer, you can expect to earn a very good living. On average, data engineers earn $91,919 to $128,171 per year.

Quantitative Analyst

Quantitative analysis is an interesting career option for data analytics graduates.

Typically employed in the financial sector, quantitative analysts utilize their methods to assist businesses and organizations in making sound financial decisions. This includes both managing risk and identifying investment opportunities that can maximize profits.

This is done by using sophisticated algorithms. For example, a quantitative analyst might develop an algorithm that triggers the purchase of a specific stock when it hits a specific price and triggers a sale of a specific stock when it hits a certain price.

By using these algorithms, quantitative analysts can do their jobs quickly, which, in turn, means that their clients can make informed decisions quickly. Often in the financial world, a matter of minutes – or even seconds – can mean the difference of millions of dollars.

In some cases, a quantitative analyst won’t work with clients specifically but will instead work behind the scenes. In this case, they develop algorithms and build computer software that analyzes financial data.

Like the other career options on this list, this one pays very well. According to PayScale, the average yearly salary is $85,069, with some quantitative analysts earning in excess of $133,000 per year.

Data Scientist

Data scientists often work closely in conjunction with many of the other professionals on this list but work more specifically on their own to identify, group, clean, and further organize large data pools of all kinds.

One key skill in this role is being able to identify patterns in massive pools of data that correlate to usable, applicable information that a company truly needs. In fact, data scientists do much the same work as data analysts but typically at a much more complex and finite level.

This job requires a very high level of technical knowledge. Not only do data scientists have to create extremely complex algorithms that organize and analyze data, but they also need to possess the ability to use programs like:

Python
R
Apache
NoSQL
Tableau

Of course, this is just a partial list – the number of programs that data scientists use is far longer. The point is, if you want to become a data scientist, you will need to be highly proficient in a number of programs to open the most career pathways.

Being a data scientist isn’t just about sitting in front of a computer, either. The most effective data scientists work as part of a larger team to help determine the course for the organization. This requires that data scientists have proven leadership abilities, excellent communication skills, and a firm grasp on statistics and linear algebra, to name a few crucial skills.

Because of the complex and technical nature of this job, it is among the most well-compensated on this list. According to PayScale, the average yearly wage for data scientists ranges from $120,290 to $148,794.

Marketing Analyst

If you have an interest in marketing, working as a marketing analyst is a great option for a data analytics graduate.

The marketing industry is certainly driven by data – data that is often broken down into tiny segments based on everything from age to toothpaste preference to spending habits (and everything in between).

As a marketing analyst, it will be your job to study consumer behavior, analyze market conditions, and even report on the marketing strategies of competitors to help your employer gain a competitive advantage for a finite number of customers.

Not only that, but marketing analysts help businesses decide what products to sell, how much to sell them for, and who the business should target for selling their products.

In some cases, marketing analysts specialize in a certain type of market – real estate or retail, for example – and as a result, develop specific expertise that can prove highly valuable to businesses in their niche.

In other cases, though, marketing analysts take a broader approach and apply the principles of data analytics to a wide range of business opportunities.

Either way, marketing analysts can expect to earn between $42,000 per year and $79,000 per year, according to PayScale.

Data Engineer

With a background in data analytics, you can also pursue a career as a data engineer.

The central task of data engineers is to build and maintain systems that can collect and organize raw data. Likewise, these systems must be designed in a way that allows for converting raw data into information that businesses and organizations can act upon. These systems might include servers, databases, and data processing systems, among others.

In other words, it’s the role of data engineers to make data as easily accessible as possible, that way colleagues like business intelligence analysts and data scientists can analyze the data and help organizations chart a course for the future.

Data engineering is often done behind the scenes. The work that data engineers do is what enables others to actually use the data that’s collected. Think of data engineering as the foundation upon which data analytics is built.

According to PayScale, the average data engineer makes $92,999 per year. However, the pay range for this position runs from $66,000 per year to more than $130,000 per year, so there is tremendous earnings upside.

Machine Learning Engineer

One of the most interesting career possibilities on this list is machine learning engineer.

Like data engineers, workers in this field have a programming background and must be highly proficient in the use of various systems in order to carry out the duties of their job.

Depending on the place of employment, as a machine learning engineer, you might be tasked with researching AI and building AI systems that automate the process of predictive modeling.

This work is incredibly valuable because it enables businesses and organizations to evaluate enormous amounts of data in a much shorter timeframe. And since it’s artificial intelligence we’re talking about, each time an operation is completed, the system learns something new. This means that the next time the operation is carried out, it can be done so more accurately and efficiently.

As a machine learning engineer, you can also expect to:

Use statistical analyses to improve models
Verify data and clean data
Training machine learning systems
Analyzing data to find deeper insights
Communicating findings to other stakeholders.

According to Salary.com, the average salary for a machine learning engineer is $122,066 per year, making it one of the most lucrative on this list.

Which Career is Right for You?

There are many different career options you can pursue as a data analytics grad. In fact, this list only begins to scratch the surface!

Given that the skills that data analysts learn in school are in such high demand, it’s safe to say that each of these careers offers the chance to join a rapidly growing subset of the workforce. If you have good grades, good command of data analytics skills, and a solid portfolio of work experience, you might even enjoy your pick of what job you want.

If you want to learn even more about data analytics work or any other matters of computer science, the International Data Engineering And Science Association is a top resource in the industry. Consider visiting their website to get additional information that will prove helpful as you plan for the future..

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