Top 10 Data Science Careers of 2023

Posted on

man on a computer sitting down looking pensive

Data science is a vast industry. Businesses and companies rely on data scientists to help them make sense of the data, find solutions to problems, and make data-based decisions. These experts use complex analytics programs, statistical methods, and more to glean information from gathered data.

Technology is becoming more complicated on the back end, more simplified on the front end, and is growing at a rapid pace. Data scientists are needed to help keep up with changing technological trends, and the US Bureau of Labor Statistics estimates this field will see a 32% growth until 2031. 

Anyone with the motivation and the right skills could enter the data science field. It’s a career that offers steady employment, financial stability, and intriguing work. Let’s take a look at the top ten data science careers.

What Is a Data Scientist?

A data scientist is a person who uses information gleaned from data to advise businesses and shareholders on significant business decisions. They sort through and clean up data, research data to find patterns, interpret the data to find opportunities and solutions, and communicate their findings to businesses and shareholders.

Essentially, a data scientist sorts through data to look for patterns and shares their findings to assist businesses in coming up with solutions to problems or opportunities for improvement. 

Data scientists perform their duties in many different ways, and several other career opportunities are available for someone in this field. 

What Skills Does a Data Scientist Need?

two people having a conversation

Data scientists must have strong skills in several fields to do their work effectively and efficiently. Being proficient in programming and coding is essential for someone working in this field. Data scientists also need skills in database software, advanced mathematics, statistics, machine learning, data analysis and visualization, and more.

Technical skills are non-negotiable for a data scientist, but some communication skills are also necessary for this job. Data scientists also need leadership skills, as they often need to take the initiative to develop solutions to problems and opportunities for improvement and present these things to business leaders. 

How Do You Become a Data Scientist?

The path to becoming a data scientist isn’t one size fits all. Technically, there are no minimum education requirements for entry-level data scientists. If you have the necessary skills and knowledge, you can work as a data scientist. 

Some start by going through a data science bootcamp, which is a short intensive training program that teaches you everything you need to know and helps prepare you for finding a job after graduation.

Others take the route of higher education. Many data scientists have a degree in mathematics, statistics, computer sciences, or a related field. Whichever path you choose, you need to have a firm grasp of programming languages, software databases, mathematics, and statistics. 

Related: How to Become a Data Scientist: A Simple Guide

Top 10 Data Science Careers

Those interested in entering the data science field may be surprised to learn that many careers fall under this term. You could be hired as a data scientist, but several other professions are also open to you. Let’s take a look at the top ten data science careers.

#1 Data Science

When you pursue an education in data science, your first instinct is probably to get hired as a data scientist! Plenty of businesses and companies need trained and experienced data scientists. In this position, you’ll likely be answering research and business questions through research conducted on gathered data.

You’ll be checking data for uniformity, correctness, and completeness. In this role, you will be expected to prepare data for use in prescriptive and predictive modeling using various sophisticated methods. Data scientists find hidden patterns in the data, predict future trends, and use this information to offer solutions and opportunities to businesses and shareholders.

Average Salary: $100,560

Related: Learn About Data Science Bootcamp

#2 Data Analyst

The work of a data analyst may sound similar to the role of a data scientist, but there are a few key differences. Data analysts implement and maintain databases, analyze data to find patterns and predict trends, and use this information to offer solutions and opportunities to businesses and shareholders.

The difference between a data analyst and a data scientist is the scope of their work. Data analysts typically have a more minor role and often work towards set goals. A data scientist, comparatively, is looking for goals to set based on the data they work review.

Average Salary: $82,360

Related: How to Become a Data Analyst Without a Degree?

#3 Data Engineer

A data engineer is responsible for putting a system into place to gather the data that data analysts and scientists use. Their role is to construct, design, develop, test, and maintain data pipelines and architecture. 

Data engineers gather data from multiple sources and organize it into one place where it’s easily accessible for data scientists or analysts. They also identify and implement ways to improve data reliability, quality, and efficiency.

Average Salary: $93,715

Related: How to Become an Excellent Data Engineer in 2023

#4 Business Analyst

The role of a business analyst is similar to that of a data analyst, with a few differences. You’re expected to bridge the gap between the IT department and the business in this role. Your goal is to analyze the data provided to you and find data-driven solutions to problems or opportunities for improvement. You then give the business your recommendations based on the data and what’s technologically and financially feasible.

Average Salary: $80,768

#5 Machine Learning Engineer

a black screen full of computer code

Machine learning engineers are highly-skilled individuals who research, design, and build autonomous software to run predictive models. A machine learning engineer will create AI systems that leverage sizeable data sets to create and develop algorithms capable of learning and making predictions.

Average Salary: $125,641

#6 Technology Program Analyst

A technology program analyst works with businesses and companies to ensure their computer systems are running correctly and efficiently. In this role, you’ll be expected to determine requirements for each system, make recommendations to optimize programs, and identify and resolve any issues.

Average Salary: $82,901

#7 Statistician

Statisticians often work in technology, healthcare, government, and research and development organization. Statisticians find trends while researching large volumes of numerical data and report their findings to the organization they work for to help make data-driven decisions. 

Average Salary: $98,733

#8 Marketing Analyst

Marketing analysts use information gleaned from data to help companies and businesses with their marketing efforts. They clean, review, and organize data to identify key trends and points, research competitors, and share their findings with their employers to make informed marketing decisions.

Average Salary: $92,534

#9 Clinical Data Manager

Most clinical data managers work in the healthcare field. This position is entrusted with deciding which data collection tools will be used to collect, organize, and manage data gathered from clinical trials.

Average Salary: $109,910

#10 Data Architect and Administrator

Data architects are responsible for building, designing, and optimizing databases. A data administrator is responsible for the operation of the database and its upkeep. Both positions require some degree of programming and coding knowledge, and each plays vital roles to most companies.

Average Salary: $144,228

Do you want to pursue a stable and fulfilling career in the data science field? Check out our data science bootcamp at TECH I.S.

Discover A Career In Data Science Through Coding Bootcamp

Data science can be a lucrative and fulfilling career. You can take your career in many directions, from working in the healthcare field as a clinical data manager to digging deeper into AI technology as a machine learning engineer. Get your career off the ground today with a coding bootcamp.