6 In-Demand Data Scientist Jobs in 2025

The data science industry is growing at a rapid pace. Technology, big data, and software are advancing every day, with plenty of jobs to reflect this demand. According to US News and World Report in 2024, information security analysts, software developers, data scientists, and statisticians ranked among the top jobs in terms of pay and demand [1].

Explore what data science is, six in-demand data science jobs with their average annual salary, and you can start in data science. 

What is data science?

Data science is the study of data. Within the field of data science, which is both a career and academic field, different roles are responsible for preparing, managing, analyzing, and processing data so that companies can solve business problems. Data scientists construct questions based on a specific data set and use data analytics and advanced analytics to find patterns, create predictive models, and develop insights that guide decision-making.

What jobs can you do as a data scientist? 6 in-demand data science jobs

Data science jobs are becoming commonplace and necessary for companies across the globe to optimize quality and financial growth. Discover some of these in-demand roles and their average annual base pay salary. 

1. Data scientist

Median annual salary (Glassdoor): $116,551 [4]

Data scientists determine the questions their team should be asking. In this job, you will figure out how to answer those questions with data, often developing predictive models and algorithms to theorize and forecast outcomes.

Data scientist job outlook

The US Bureau of Labor Statistics predicts that data science jobs will experience 36 percent growth between 2023 and 2033 [2]. Operations research analyst (or data analyst) jobs will likely grow by 23 percent, another high-growth job title [3].

Due to the high demand and technical skill set, jobs in data science tend to pay well. Data science is penetrating nearly every industry, including health care, retail, and technology, so you have plenty of options to find your niche. If you're interested in this field, you might consider boosting your skills in statistics, mathematics, programming, coding, and software development and researching what to expect.

2. Data analyst

Median annual salary (Glassdoor): $84,949 [5]

A data analyst collects, analyzes, evaluates, reviews, organizes, and visualizes data. You would organize the data and perform statistical calculations to find trends that can solve problems for a client or your employer and inform important business decisions.

3. Data engineer

Average annual salary (Glassdoor): $105,727 [6]

Data engineers build systems that can automatically collect, store, manage, and analyze data sets so that other data scientists and mathematicians can spot trends and patterns for interpretation. The systems make data easy to digest, so it can help a company or customer. 

4. Data architect

Average annual salary (Glassdoor): $139,571 [7]

Data architects create plans for systems to manage and organize data. As a data architect, you map out a company’s plan for solving a particular issue and then construct systems that data scientists use to spot trends and patterns.

5. Machine learning engineer 

Average annual salary (Glassdoor): $121,807 [8]

Machine learning engineers design the architecture for artificial intelligence (AI) programs to interact with large data sets. You will work with other data scientists and programmers to create AI programs that can detect patterns, filter data, and perform algorithmic calculations. The programs use AI to automate processes that help customers make choices and make their lives easier.

6. Business intelligence engineer

Average annual salary (Glassdoor): $108,048 [9]

Business intelligence engineers design, install, maintain, and develop data systems that analyze large chunks of data specifically for financial and business purposes. In this position, you create interfaces that allow employees to easily access and understand data. As a BI engineer, you may also work on other systems, such as databases and dashboards, that users interact with to evaluate data across departments.

How to become a data scientist

To start, take a look at the online courses, boot camps, workshops, and certifications out there. Many paths exist when becoming a data scientist. However, you can find courses and degree programs from leading universities on Coursera and refer to this archive of Coursera's data science articles, Data Science Jobs: Resources and Career Guide.

1. Boost your skills.

Whether you are just starting your career in data science or switching from another field, you'll want to develop the necessary skills. Start by researching and deciding on a type of data science you'd like to try out. Read blogs, listen to podcasts, and get a better grasp of the field as a whole.

For many data science jobs, a bachelor's degree in a relevant subject such as IT, computer science, or mathematics is a great start. Some employers like to see a master's degree for senior-level roles. However, if you hold a bachelor's in an unrelated major or don't have a university degree at all, don't fret. Plenty of online courses and certificates exist that you can take while working another job. Plus, employers these days are much more open to hiring candidates from less conventional backgrounds. If you have the time, you might consider enrolling in a boot camp. The possibilities are endless.

2. Earn a certification.

A great way to start pursuing a career in data science is to get certified in specific skills and systems. Data science certifications can demonstrate your expertise. If you have a specific position in mind, you can usually see a list of the types of systems required in the job description, which can help guide you on what certification is best for your career and interests. Some possible certifications include:

• Certified Analytics Professional (CAP)

• SAS Certified Big Data Professional 

• Oracle Business Intelligence (BI)

• IBM Data Science Professional Certificate

3. Gain work experience.

If you are completing a degree in a data science-related subject, some of your classes will be practical projects requiring the completion of hands-on activities and projects. Use these to build a portfolio that you can present to an employer. 

Another way to get some relevant work experience is open-source development. Open-source programs allow users access to the source code of their software, so you can apply your programming knowledge to an open-source program and make changes to improve the software. Applying your skills to applications that people use every day is a great way to showcase your knowledge and understanding of the software. 

Hackathons are another excellent way to test your skills and collaborate with a team on a project. These competitions can provide industry experience for someone looking to get into the data science field because they replicate the teamwork, pressure, and type of work that data science professionals encounter on a regular basis.

Start your data science career with Coursera

Many different kinds of data scientist jobs exist, and offer various paths you can take to start your career. Coursera is a great place to start exploring a certificate that is right for you, with many different Professional Certificate programs from top companies and universities in the industry. Consider elevating your career in data science with an IBM Data Science Professional Certificate or a Google Data Analytics Professional Certificate.