Data science training can prepare you for a career as a data analyst, data scientist, data engineer, and more. Throughout your studies, you will learn how to collect and organize data, and how to discover data-backed insights. Data scientists bring together their skills in statistical analysis, computer programming, and communication to help businesses make crucial decisions.
This guide explores data science career possibilities that you can pursue after completing a degree or specialized training in a data science bootcamp. You can learn about data science salary potential and common industries that employ data scientists.
What Is Data Science?
Businesses collect data on a variety of performance indicators and business needs, tracking information such as product development costs, profit margins, customer feedback, and social media engagement. With the right tools, data scientists can organize and use this data to improve company efficiency, develop new products, and resolve customer concerns.
The Bureau of Labor Statistics (BLS) projects 15% growth in the employment of computer and information research scientists between 2019 and 2029, as well as 10% growth for database administrators. Data professionals work in a variety of industries, including technology, finance, healthcare, retail, and manufacturing.
What Do Data Scientists Do?
Data science involves collecting, cleaning, storing, accessing, and analyzing data. This work typically includes computer programming, database development and management, and data visualization.
Working in data science requires an understanding of statistics and algorithms so that you can verify your data, evaluating it for completeness and accuracy. Programming languages such as Python and SQL help data scientists mine large datasets for information and patterns that can help businesses improve manufacturing efficiency, understand consumer behavior, and evaluate the impact of policy changes.
Data scientists often develop models and create visualizations, such as charts and graphs, to help communicate their findings to business leaders and colleagues. Data scientists must understand the strengths and weaknesses of various visualization methods to choose the best option for their data.
Data Science Career Outlook
Demand for data scientists appears to be growing. The BLS projects that jobs for computer and information research scientists will grow 15% between 2019 and 2029. In 2019, LinkedIn identified data science as its most promising job, and data science ranked third on Glassdoor's list of best jobs in 2020.
Data science bootcamps have evolved to help meet this industry workforce need. While some employers may prefer candidates with a degree in computer science, completing a top bootcamp can help you develop the skills necessary to succeed as a data scientist. Bootcamps also focus on hands-on projects and help you to develop a professional portfolio that can allow you to showcase your skills and knowledge.
Data science careers typically offer high earning potential. The BLS reported an average salary of $100,560 for data scientists in 2019. Additionally, according to PayScale, average data science salaries range from $85,540 a year for entry-level roles to more than $135,000 for veterans in the field.
Data Science Career Paths
Data science encompasses multiple areas of specialization, including database architecture, machine learning, and data visualization. Data science bootcamps offer opportunities to delve into these various specialties, allowing students to create relevant portfolios and document job-specific knowledge and skills. Below, learn more about the many exciting career paths available in the data science field.
- Data Analyst
Data analysts help collect and analyze data to solve a specific problem or answer a specific question. They work closely with various departments to understand the problem and collect relevant data. They may develop surveys and recruit survey participants, ensuring a statistically relevant sample size. Once they collect their data, they often use graphs or charts to present it. They may also recommend data collection measures to track project effectiveness over time.
Data analysts use various software in their work, including Microsoft Excel and SQL databases. They often have an understanding of programming languages such as Python and Java. Strong teamwork and communication skills are also important to this job.
PayScale reports data analysts earn an average salary of $60,890. Entry-level analysts earn $55,460 on average, while experienced analysts earn $70,980. Employers seek relevant work experience and training, such as attending a data science bootcamp or earning a degree in computer science.
- Data Scientist
According to PayScale, data scientists earn an average salary of $96,160. These professionals typically work in office settings, primarily in the information technology (IT) department of an organization. They often work in teams to manage their organization's data collection and storage needs.
Their duties include designing and building processes organizations can use for data modeling, data mining, and data production. They often use the latest software and programming tools to create custom datasets, and identify and analyze industry trends. They also help translate this information into easily understood presentations. They may write reports and create graphs and charts.
Most companies consider a candidate's work history and education when hiring for a data science position. A degree in computer science, particularly an advanced degree, can provide a competitive advantage to a candidate. Companies also look for expertise in areas like data analysis, big data, and machine learning.
- Data Engineer
Data engineers develop and prototype computer code designed to maintain/organize large datasets and identify trends in the data. They need experience designing databases and a familiarity with multiple coding languages, such as Python and Java. These engineers often work in teams and must carefully document their work to better collaborate with other team members.
PayScale reports that data engineers earn an average salary of $92,300 annually. Entry-level data engineers take home an average of $77,410, while experienced data engineers earn $118,950.
Data engineering professionals often hold a degree in computer engineering or computer science. Work experience and graduating from a data science bootcamp may be sufficient to secure an entry-level position, though some employers may still require a college degree.
- Data Architect
Data architects design databases that ensure essential data remains secure and accessible to users. This career requires advanced knowledge of computer coding languages, particularly SQL and XML. Data architects must also understand how their organization collects, stores, and uses its data, and they must design databases and data processes that meet organizational needs.
Data architects often work with departments and staff outside of IT; therefore, they must have good verbal communication skills and be able to explain complicated data collection processes to nonexperts. These architects create workflows and supporting documentation, so good writing skills are also necessary to their success.
PayScale reports an average salary for data architects of $119,090. Entry-level data architects earn $68,690 on average, while experienced data architects earn $125,180. Most data architects have at least a bachelor's degree in computer science or computer engineering because of the advanced skill set required, and many have advanced degrees.
- Business Intelligence Developer
These data experts help fine-tune IT processes and programs. They may debug software or test code before implementing new tools. Much of their time involves researching organizational problems and developing solutions. They share their work through reports, charts, and graphs, communicating with technical and nontechnical staff and executives.
Professionals working in this role earn an average salary of $80,180, according to PayScale. Entry-level jobs pay an average of $59,970, while individuals with many years of experience report an average salary of $97,480. Most business intelligence developers work full time in an office setting. They may hold managerial responsibilities within an IT department.
These roles typically require both a degree in computer science or computer engineering and substantial work experience in the field.
What Kind of Skills Do Data Scientists Need?
Successful data scientists combine their technical skills and programming proficiency with critical thinking and problem-solving abilities. Soft skills such as teamwork, communication, and determination ensure data scientists can tackle complex problems, communicate important business insights, and work collaboratively with multiple departments in an organization. Below, learn more about key skills for a data science career.
Mathematics forms the basis of data science. To work in a data science career, you need a solid understanding of algebra and statistics. Understanding the mathematical principles behind computer algorithms helps you know how to write code and troubleshoot problems that arise. Understanding concepts in discrete math, graph theory, and information theory can also help you succeed in data science.
- Computer Programming
Data scientists use a variety of programming languages and software programs to do their work. Employers may seek data scientists who are familiar with database management software such as Oracle Database, MySQL, Apache Hive, and MongoDB. Data scientists are often proficient in one or more programming languages, with common languages for data science including Python, SQL, and R.
- Complex Problem-Solving
Much of the information data scientists use must be "cleaned" — edited and sorted — in order to be useful. Critical thinking skills help data scientists isolate the most useful information from a variety of data types. Data scientists must also critically evaluate data, looking for trends and patterns that can inform business decisions.
Data scientists must communicate their findings to others, such as business managers, stakeholders, and policymakers. They often do this through the use of data visualization, such as charts or graphs. They must also understand how to communicate their insights clearly and concisely to an audience that may not understand statistical analysis.
Cleaning large datasets and writing computer code can sometimes be tedious. Data scientists must possess the focus and determination necessary to keep working on a problem or task until they have resolved it.
Why Pursue a Career in Data Science?
Do you enjoy math? Can you identify patterns? Can you communicate effectively with people who may not understand statistics as well as you?
These questions can help you determine if you will enjoy a career in data science. This career attracts individuals who enjoy analyzing information, including quantitative data. Because companies use this data to make decisions, you also need an understanding of business strategy and principles.
Data science requires a commitment to lifelong education. The field is continuously evolving, and data scientists must stay up to date on these changes and be willing to learn new skills throughout their careers.
Where Can You Work as a Data Science Professional?
The BLS reports that the computer systems industry hires the most data scientists, but data professionals can find employment in many industries, including financial services, healthcare, and business management. The aerospace products and parts manufacturing industry offered the highest average salary for data scientists in 2019 — $143,670.
You can find data science career opportunities in almost every state.
California is home to the most data scientists, with 4,690 professionals in the state. Other top states for employment include Illinois, Texas, and New York. New York reports the highest average salary for data science professionals, who earned an average of $125,170 in the state in 2019. Workers in North Carolina and Maryland also earned particularly lucrative wages.
While cities with a busy technology sector report the highest numbers of data science jobs, you can find data science career opportunities in almost every state. With the right skills, you may also find remote work as a data scientist.
Frequently Asked Questions for Data Science Careers
- Is data science a good career?
If you enjoy working with numbers, finding patterns and trends, and helping businesses make important decisions, data science may be an exciting and rewarding career choice. The field includes a variety of subspecialities that can build upon your skills in communication, visualization, and computer programming.
- Is there a demand for data scientists?
Yes. The BLS projects 15% employment growth for computer and information research scientists between 2019 and 2029. Additionally, LinkedIn named data science the most promising job in 2019. More and more businesses need the expertise of data scientists to make informed business decisions. Cloud computing and software-as-a-service providers have also expanded their operations to include data science services for small and midsize companies without IT departments.
- Can I be a data scientist without a degree?
Yes, immersive data science bootcamps can prepare you to enter some data science careers in a few short months. These programs emphasize hands-on learning and job-specific skills. Bootcamps often focus on building a professional portfolio that demonstrates your expertise. Many programs provide job placement assistance, as well. You can find online, in-person, and hybrid data science bootcamp options.
- Does data science pay well?
Data scientists earned an average annual salary of $100,560 in 2019, though pay can vary based on location, industry, years of experience, and specialization. PayScale reports average salaries ranging from $85,540 for entry-level data scientists to $136,650 for veteran data scientists.