Data Scientist Job Description

If you are considering a career that combines knowledge of mathematics and science with the use of data, you may be interested in becoming a Data Scientist. Data Scientists analyze data sets to gather actionable insights that help organizations reach their goals. In this article, you will learn more about what a data scientist does, the job requirements, job responsibilities, what Data Scientists earn, and more.

What is a Data Scientist?

A Data Scientist extracts meaning from data sets to identify opportunities for improved performance and to make recommendations to help organizations advance toward their goals. The responsibilities of a Data Scientist include extracting valuable data from data sources, leveraging machine learning algorithms, improving the procedures used to collect data, cleansing data, validating the integrity of the data, and presenting findings to stakeholders. 

Most Data Scientists work full-time in an office environment or remotely. A Data Scientist can find work in almost any field including corporations, government agencies, nonprofits, technology, retail, research institutions, and more. They may work as part of a data science team that includes Data Analysts and Business Intelligence (BI) professionals. They may also work closely with Data Engineers and Developers.

Data Scientists’ day-to-day responsibilities will differ based on the organization they work for, however, common responsibilities include detecting patterns and opportunities from data, presenting findings to stakeholders, building data models, and automating collection processes.

Job Requirements

Data Scientists must have a strong foundation in math and science to manage, understand, and use data sets. Most Data Scientists will have a bachelor’s degree in computer science, engineering, or another scientific field. However, university is not the only means by which one can learn data science skills. Data science bootcamps and data science certificate programs that combine theoretical knowledge with hands-on experience can provide the foundation to begin a professional career as a Data Scientist. One way to provide prospective employers with solid evidence of your data science skills is to create a professional portfolio with examples of your work.

Earning a data science certification also helps your resume to stand out and demonstrates to employers that you meet the rigorous standards of nationally-recognized data science certifications such as CAP, DASCA, CDS, and SAS. CAP stands for Certified Analytics Professional. The Associate Certified Analytics Professional certification (aCAP) serves as an entry-level certification for professionals educated in data analytics but may lack professional experience. Earning an aCAP certificate is also a necessary prerequisite to earning a CAP certification and therefore can serve as an excellent first certification to earn.

Read more about the job requirements for a Data Scientist.

Job Responsibilities

The daily job responsibilities of a Data Scientist vary based on the type of organization you work for, your rank within the organization, and whether duties are divided between team members. Some job responsibilities of a Data Scientist include: 

• Extracting valuable insights from data to improve marketing effectiveness and increase sales
• Develop processes for gathering, processing, and analyzing data
• Communicate with team leaders to make recommendations based on findings
• Use machine learning tools to create and optimize classifiers
• Preprocess structured and unstructured data
• Develop machine learning algorithms and predictive systems
• Collaborate with IT and business teams
• Clean and process data
• Verify the integrity of the day
• Integrate data
• Store data 
• Solve problems and challenges to meet organizational goals
• Make adjustments based on feedback

Skills

The first step to becoming a Data Scientist is to learn the necessary skills for gathering, managing, and interpreting raw data used by organizations to achieve their goals. Data Scientists must develop several mathematical and scientific skills, including a thorough understanding of machine learning and programming languages used in data collection, management, and analysis. Such skills include understanding: 

• SQL
• R programming
• Python
• File management
• Machine learning and algorithms
• Natural language processing
• Linear algebra
• Calculus
• Statistics
• Probability

Data Scientists often create data visualizations to communicate findings to stakeholders, so they must also understand how to use data visualization tools such as Tableau. A successful Data Scientist knows how to work closely with others, focus on details, recognize patterns, and develop solutions to problems. A Data Scientist must also develop the communications skills necessary to relay recommendations and findings to stakeholders.

Read more about what skills you need to become a Data Scientist.

Why Do Businesses Need Data Scientists?

Understanding data is crucial to understanding an organization’s current state, identifying areas for improvement, planning for the future, and helping organizations meet their goals. Data Scientists understand how to gather, process, and extract valuable information from data. They help leaders within the organization identify problems, collect relevant data, make sense of that data, and solve problems based on the facts. Data Scientists also help businesses leverage artificial intelligence and machine learning to gather such data, improve customer experiences, automate certain processes, improve productivity, and help a business scale up. Data Scientists can, for example, identify which products or services sell best, how a business fares compared to the competition, and opportunities for the business based on predicted future outcomes.

Where Do Data Scientists Usually Work?

Data Scientists have many options when choosing a field to work in. Data Scientists work for corporations, technology companies, startups, government agencies, nonprofits, research institutions, and more. They typically work full-time in either an office environment, remotely, or in a hybrid role. Well-known companies that hire Data Scientists include IBM, Oracle, Splunk, Somo Logic, and Helium 10. 

Data Scientist Salary and Job Outlook

Have you ever wanted to start a career in data science but wondered if the job prospects will make the career change worthwhile? Both the average salary and projected job growth of Data Scientists make this a promising career. The U.S. Bureau of Labor Statistics found the median pay for Data Scientists, as of 2021, amounts to over $131,000 per year. The job outlook for Data Scientist is far higher than the national average with a projected job growth of 36% in the coming decade. 

To become a Data Scientist, you will need a solid foundation in math and science, especially computer science. You will also need to understand data visualization tools, machine learning, certain programming languages, and other skills needed to gather, manage, and interpret data sets for organizations. At first, learning such skills might feel overwhelming, but the potential for a lucrative and rewarding long-term career make the investment of time and effort well worth it.

Read more about Data Scientist salaries and the job outlook for a Data Scientist.

How Long Does it Take to Become a Data Scientist?

How long it takes to become a Data Scientist depends on your existing knowledge of mathematics and science, any relevant experience you have, and the educational path you choose. 

Earning an undergraduate degree in a relevant field typically takes around four years. Additional time is required to earn a master’s degree or Ph.D. Graduate degrees such as a master’s and Ph.D. can take anywhere from one to eight years to complete. 

Accelerated learning options such as data science certificate programs can take anywhere from one month to half of a year depending on if you enroll in a part-time or full-time program.

If you have a four-year degree already, you may be able to enroll in an accelerated program through a college or university that focuses on teaching you the skills needed to start a career in data science. Some schools also accept professional experience in lieu of certain classes. 

The fastest way to learn data science skills is through a full-time enrollment course either in-person or live online. Both class types connect you to an expert instructor in real-time, meet at specific times throughout the week, may include assignments completed outside of class, offer the ability to collaborate with classmates, provide critical hands-on experience to sharpen your skills and help retain information from readings and lectures, help you build a professional portfolio, and may provide additional services such as one-on-one mentorship and job search assistance. One thing to keep in mind is that while a full-time course will allow you to earn a certificate at the earliest date, the number of hours required for class and outside assignments make it difficult to commit to if you have another job. For those with full-time jobs looking to learn on evenings and weekends, a part-time data science course can teach you all the same skills as a full-time course, but at a more manageable pace. 

You can explore part-time and full-time data science classes using Noble Desktop’s Classes Near Me tool. 

Data Scientist vs. Similar Career

The job titles of Data Analyst and Data Scientist can sometimes cause confusion. This is because both positions work closely with data and there can be some overlap between the two jobs depending on the size and nature of an organization or the data science team. Typically, though, the difference between the two jobs is that a Data Analyst analyzes data to identify patterns and trends and create data visualizations such as graphs and charts, which are duties a Data Scientist might also perform, but a Data Scientist has additional responsibilities that go beyond analyzing that data. Such responsibilities include working on predictive models, using machine learning algorithms to improve data gathering and management processes, making recommendations to stakeholders based on findings, cleansing data, verifying the integrity of data, using artificial intelligence to predict future outcomes, integrating data, storing data, and making adjustments to processes based on feedback from stakeholders. 

Put another way, a Data Analyst focuses on making sense of existing data while a Data Scientist works with existing data and on methods of collecting new data. A Data Scientist role may also require more scientific and mathematical knowledge than that of a Data Analyst role.

Learn the Skills to Become a Data Scientist at Noble Desktop

If you are looking to start a new career in data science, you might think the only way for you to become a Data Scientist is by enrolling in a four-year university or pursuing other costly and lengthy educational options. However, there are many alternative methods available to help you transition into a data science career, including data science bootcamps and certificate courses designed to help working professionals gain the skills needed to obtain an entry-level job as a Data Scientist. Exploring in-person and live online data science bootcamps and certificate programs can help you find the class that meets your career goals, budget, and schedule. The first step to finding the class that fits your needs is to understand the differences between in-person classes and live online classes. 

In-person data science classes meet in a traditional classroom setting at a physical location. In-person classes have the advantage of providing all necessary equipment, such as computers and software, and allowing students to network with local professionals such as your classmates and instructor. You also have the advantage of learning from an expert instructor face-to-face. The primary drawback to in-person courses is the extra time and money required to commute to the physical learning location. Live online data science classes offer many of the same benefits as in-person classes, including the ability to learn in real-time from an expert instructor. You can also collaborate with classmates, and you have the advantage of learning remotely. 

Noble Desktop offers several different in-person and live online data science classes that can help you start a career as a Data Scientist. The Python for Data Science Bootcamp teaches students foundational programming concepts and how to handle different data types, use conditional statements to control the flow of a program, use Scikit-Learn, Matplotlib, Numpy, Pandas, and other Python libraries and tools. Noble’s Data Science Certificate program and Data Analytics Certificate program provide a deep dive into the topics and skills essential to launching a career in data science or data analytics and offer one-on-one mentorship and job search assistance. All Noble Desktop classes provide students with hands-on experience, flexible financing options, setup assistance, a free retake, small class sizes, and real-time guidance from an expert instructor.

Learn more about Noble Desktop’s in-person and live online data science classes.

You can also learn more about data science careers and data science learning options with Noble’s free Data Science Learning Hub.

Key Takeaways

• Data Scientists create and optimize data collection processes, make sense of structured and unstructured data, and use these insights to improve and help organizations meet their goals.
• A Data Scientist should understand computer science, programming languages like R, Python, and Java, and should understand calculus, linear algebra, statistics, and other mathematical subjects. 
• The U.S. Bureau of Labor Statistics found the average annual salaries for Data Scientists are around $130,000. Project job growth for Data Scientists is 36% for the coming decade. 
• Data Scientists can work in a wide range of fields including research institutions, technology companies, large corporations, startups, government agencies, and nonprofits.
• A Data Scientist typically works full-time in an office, remotely, or in a hybrid capacity.
• Data Scientists may work with other members of a data science team and regularly collaborate with IT and business teams. 
• Data Scientists regularly report their findings and recommendations to stakeholders within the organization.
• How long it takes to become a Data Scientist depends on several factors, including the educational path you choose. You may choose to obtain a four-year degree, a graduate degree, or enroll in either a part-time or full-time data science certificate program lasting from around one to six months.
• You can receive comprehensive training to become a Data Scientist through an in-person or live online course with Noble Desktop.