what is a data scientist?

More than ever, companies, governments and other institutions rely on data to make their decisions. This data can track everything from traffic flows to consumer purchasing habits to weather patterns. But raw data doesn't help decision-makers choose the best options; someone has to process and analyze it. This task falls to data scientists, who are expert analysts with deep knowledge of technology and statistics.

Data scientists combine these analytical skills with knowledge of the topic they're analyzing to create models based on the data they study. Using these models, data scientists attempt to understand past and present situations and even predict future behavior.

Like all scientists, data scientists not only carry out their analysis but also present their findings to others. Whether that means communicating with corporate management, the government or the public, a data scientist must provide clear, useful information. This means that communication skills are a vital part of a data scientist's job.

Would working in the tech or IT industry as a data scientist suit your analytical mind and knowledge of statistics? Then read on to find out what competencies and qualifications you need to thrive in a data scientist role.

data scientist jobs near you

average data scientist salary

As a data scientist, you are a highly skilled professional, and your compensation reflects that fact. The median salary of a data scientist was $100,910 in May of 2021. However, because data scientists work in a wide range of different institutions, salaries can vary depending on area of specialization and your employer.

Would you like to know how much a data scientist earns? Where the highest salaries are paid to a data scientist? Then check out this salary page and find out all about the salary of a data scientist in the USA.

two colleagues having a conversation, monitors showing data in the foreground
two colleagues having a conversation, monitors showing data in the foreground

types of data scientists

Within the world of data science, you can pursue a number of different specializations. These might include:

  • data engineering: A data engineer builds and maintains the frameworks used for analysis by consolidating, cleansing and structuring data collected from multiple sources.
  • database management and architecture: A step up from a data engineer, this type of specialist is responsible for actually designing the digital framework of a specific organization.
  • operations data analysis: Less technical than other data scientists, an operations data analyst uses statistical software to evaluate and solve business-specific problems.
  • marketing data analysis: Using analytic tools, a marketing data analyst is specifically concerned with measuring and improving the effectiveness of a marketing campaign, particularly in terms of ROI and with consideration of marketing trends.
  • machine learning: A growing field within data science, data scientists who specialize in machine learning create algorithms that work without direct human participation. These automated systems can work many times faster than humans, making them ideal for dealing with large data sets.
  • artificial intelligence: Artificial intelligence (AI) is another specialist area within data science. Although related to machine learning, AI has its own methods and principles, and many data scientists specialize in one or the other.

working as a data scientist

If you're interested in finding out what a job as a data scientist involves, read on. You'll find out about the daily work of a data scientist as well as your work environment and prospects.


data scientist skills and education

Degrees adjacent to the field of data science include, but are not limited to, computer science, engineering, physics, and, of course, mathematics. However, even degrees in fields such as economics and psychology can lead to a career in data science, as these areas of study often rely on statistical models.

The majority of data scientists enter the field with a college degree. Most data scientists have, at minimum, a bachelor’s degree, but some of the highest-paying data science jobs require a master’s degree or doctoral degree. Because data science heavily relies on algorithms, deep analytical thinking and work with complex systems and statistics, hopeful data scientists should be well-learned in the various STEM fields.

That said, not holding a degree in STEM does not bar you from pursuing a career in data science. Because the demand for data science jobs is projected to greatly increase for the foreseeable future, there are opportunities for those without the credentials to set themselves on a path toward a data science career. These opportunities include certifications and “boot camp” courses from accredited universities.

An apprenticeship, combining classroom learning with workplace training, can also lead to a job in the field.

skills and competencies

As a data scientist, you will need an abundance of both quantitative and communicative skills. Due to the scope and nature of the work, a data scientist is almost like a jack-of-all-trades within the tech/marketing industry. Here are just some of the skills and competencies you should have as a data scientist:

  • strong analytical skills: Data scientists must be able to analyze large amounts of data and draw insights from it.
  • programming skills: This field requires working knowledge of various computer programming languages.
  • statistical knowledge: Data scientists need a strong understanding of statistical methods and how to apply them to analyze data.
  • data visualization skills: Those in this field must be able to create clear and concise visualizations to communicate their findings effectively.
  • communication skills: These professionals should be able to clearly communicate their findings to both technical and non-technical colleagues.
  • creativity: Good data scientists are always exploring new ways to solve problems.
  • time management skills: Those working in this area should demonstrate the ability to manage their time and prioritize tasks effectively.
  • teamwork and collaboration: Data scientists must work closely with other teams, such as business stakeholders and IT professionals, to ensure that their work aligns with the goals of the organization.

There is more to being a data scientist than simply analyzing data and constructing models! You will need a plethora of skills and be willing to be a team player!

hand holding stylus, navigating on a tablet screen
hand holding stylus, navigating on a tablet screen

FAQs about working as a data scientist

Here you will find answers to the most frequently asked questions about data scientists.

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