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 analyse 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 analysing 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 behaviour. 

what do data scientists do?

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 tech and 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

average salary of a data scientist

As a data scientist, you are a highly-skilled professional, and your compensation reflects that fact. The National Careers Service reports that a starting data scientist typically earns around £30,000 per year, while a more experienced data scientist can earn £70,000. Because data scientists work in a wide range of different institutions, salaries can vary depending on the employer. For instance, starting data scientists in a corporate environment may earn more than their counterparts in academia but lack opportunities to do their own research. 

Female with blue headphones around her neck looking at a screen
Female with blue headphones around her neck looking at a screen

types of data scientist

Within the world of data science, you can pursue a number of different specialisations. 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 organisation.
  • 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 specialise 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 specialise 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. 


education and skills

Most data scientists enter the field by studying it at university. Subjects that lead into careers in data science include maths, statistics, and computer science. Some universities even offer degrees specifically in data science. In addition, some data scientists enter the field after doing undergraduate degrees in fields that involve significant data analysis work. These subjects include STEM fields like physics or engineering but also other statistics-heavy areas such as psychology or economics. Graduates in other fields can also transfer to data science by doing a conversion course. This type of master's degree is intended to bring graduates in other subjects up to speed in a new field quickly. 

Although a degree in a related subject is the most common way to begin a career in data science, it isn't the only one. An apprenticeship, combining classroom learning with workplace training, can also lead to a job in the field. This will be a degree apprenticeship, which culminates in a qualification equivalent to a university degree. 

skills and competencies

A data scientist's skill set includes both quantitative and communication skills. The core of the work is data analysis and interpretation. So:

  • your most important asset is an analytical mindset and a drive to solve problems using data
  • you should have experience with databases and database analysis tools. 
  • your knowledge of software packages and programming languages is an important factor; you will work to expand and update this knowledge throughout your career. 

However, there's more to being a data scientist than simply analysing data and constructing models based on it. In order for your findings to be useful, you have to be able to communicate them:

  • this could mean verbal communication in meetings or lectures. 
  • alternatively, you could communicate your work in written form, writing reports, articles or even books. 
  • your ability to explain your work, especially to people who lack your background in data, is crucial to your success. 
smiling female looking away
smiling female looking away


FAQs about working as a data scientist

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