How To Become a Data Scientist
How To Become a Data Scientist
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Virtually every industry can benefit from the insights provided by data scientists. From retail and business to healthcare and banking, organizations rely on data to anticipate what customers need and want. This helps organizations to optimize their strategy and stay competitive. Data scientists can explore careers across many sectors and use their skills to make data-driven decisions.
Some key industries that hire data scientists include:
Business
Business professionals use data science to improve efficiency, forecast market behavior and optimize supply chains.
Healthcare
The healthcare industry looks for ways of making healthcare delivery more efficient, better for patients and less costly.
Transportation
Data scientists working for the transportation industry assess how to reduce traffic jams and improve the customer experience on public transportation.
Banking
The banking industry uses data science technology to personalize customer experiences and inform decision making.
Retail
Data analytics is integral to developing accurate insights about consumer trends.
Insurance
The insurance industry relies on data scientists to identify fraudulent activity, assess customer risk profiles and make decisions about policy pricing.
Median annual wage for data scientists as of May 20243
Estimated growth for data scientist jobs expected from 2024 to 20344
When working toward becoming a data scientist, choosing the right program is important. GCU’s programs offer hands-on experience, practical application and capstone projects that can help prepare you for a career in data science.
A bachelor’s degree can help you build a solid foundation in computer science and data analysis principles. You’ll explore how big data works, critically examine current algorithms and techniques and develop original methodologies.
A master’s degree program will take a deep dive into the critical topics that aspiring data scientists need to know, such as data mining, advanced statistics and machine learning operations.
Doctoral programs can allow you to test new methodologies and experiment with new data science technologies. These programs help familiarize you with the emerging developments in the field, teaching advanced skills and in-depth knowledge.
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The daily responsibilities of a data scientist depends largely on the type of organization they work for. These professionals must first thoroughly understand the objectives of their organization or department and then assess how data analytics can be used to achieve those goals.
The specific tasks of a data scientist may include the following:
Data Modeling
Data scientists design data modeling processes to extract insights from complex datasets.
Develop Algorithms
They develop algorithms and predictive models to forecast trends and identify patterns.
Processing Data
Data scientists process the data to “clean” it and extract the relevant data.
Data Analysis
They conduct data analysis using techniques like machine learning, statistical modeling and artificial intelligence.
Evaluate Results
They evaluate the data analysis results and present insights to organizational stakeholders.
There is no universal requirement regarding the exact type of degree a student should earn to become a data scientist. However, mathematics, computer science or business analytics degrees are generally preferred by employers.2 Students in data science degree programs will study how to use existing data science methodologies, techniques and algorithms.
A typical data science or computer science program covers topics such as:
Large scale information systems
Discrete mathematics & differential equations
Computer architecture
Developing algorithms
Machine Learning Operations (MLOps)
Application of data science techniques
A data scientist is a professional that analyzes complex data sets. They use a number of statistical methods and programming skills to collect data, analyze it and communicate findings through data visualization. They collaborate with businesses and organizations to drive growth and solve problems through data-driven decision making.
Students who have a knack for numbers, a passion for technology and a desire to help organizations solve complex problems might consider pursuing a career in data science. This growing field has implications for various industries, from technology to national security. Explore this career guide to learn more about what data scientists do and the pathway for becoming a data scientist.
According to the BLS, data scientists are ranked 4th in occupations with the highest projected percent change of employment between 2024 – 2034.1
The path to becoming a data scientist often starts with a solid background in mathematics, statistics and computer science, often developed through a bachelor’s or master’s degree. This formal education is essential for building the analytical, technical and problem-solving skills needed to enter the profession. Staying committed to lifelong learning, through earning a degree or certificate, can help you stay current in a field that is constantly growing and developing new technologies.
Earning a high school diploma is the first step in your educational journey. High school students who are interested in pursuing the data scientist career path are advised to speak with their school counselor about their career goals. It may be possible to adjust your schedule to better prepare, such as by adding more mathematics classes. Courses in computer science, particularly software applications, will also be helpful.
It is possible to land an entry-level job in data science with a bachelor’s degree. However, graduates who are new to the field are likely to find that many jobs in data science do require a master’s degree. Even if a master’s degree isn’t a strict requirement, employers often prefer to hire data scientists who hold one.1
A master’s degree, like an MS in Data Science, is recommended for aspiring data scientists who earned a bachelor’s degree that wasn’t specifically focused on data science.
For those interested in developing skills to position yourself for potential leadership roles, or applying data science in strategic business contexts, a Doctor of Business Administration can help you develop advanced analytical expertise.
Internships are a great way to get started in data science, especially if you are a recent graduate with little to no experience in the industry. Completing an internship can help you gain practical skills by applying your knowledge to real scenarios and business challenges under the guidance of a supervisor. You can also work on building your professional network and developing your resume.
Earning a professional certificate can help you fill your skills gaps and stay competitive in the industry. These programs teach specialized skills in specific programming tools.
Common data science certifications include:
Data scientists who want to grow in their careers might be interested in becoming a senior data scientist, a director of data science or a computer and information systems manager. The degree requirements and experience needed for these roles may vary by employer.
Data scientists need a mix of soft and technical skills to be effective at solving problems and working with complex data sets.
These skills include:
Predictive modeling
Linear regression and multivariate analysis
Data mining algorithms
Theories, design and creation of software applications
Problem-solving
Critical thinking
Communication
Adaptability
Explore the skills, tools and steps you need to start your journey toward a data science career.