Data Analyst Job Profile

Data analysts gather and organise data, using it to reach meaningful conclusions that will benefit their employer. The role is integral across almost every sector, from sales and social media to the mainstream media and government. The data-driven insights analysts bring to an organisation can be valuable to employers who seek information pertaining to their customers’ or users’ needs.

If you’re thinking about becoming a data analyst, we’ll tell you everything you need to know about the role and how it fits into a larger career in data science.

What is a data analyst?

Data analysts use specialised computer software and calculation applications to establish numerical patterns and emerging trends in their specific industry. They regulate, normalise, and calibrate the data so that it can be extracted, used in isolation, or input into a broader data set while maintaining its integrity.

From this numerical foundation, data analysts organise and interpret the data, before presenting their findings to management in a concise, engaging manner using graphs, charts, tables, and graphics.

Due to their proficiency with numbers, data, and trends, data analysts are often asked to advise department heads and project managers on how their insights can improve performance in specific parts of the business.

Responsibilities

Your responsibilities as a data analyst will vary depending on where you’re employed and what level of experience you have. Despite this, almost all data analysts will have a broad role that involves some or all of the following responsibilities:

• Identify areas to increase efficiency and automation of processes

• Develop, produce, and track key performance indicators

• Liaise with internal and external clients obtain a comprehensive view of data content

• Gather and document specific business requirements using appropriate tools and techniques

• Mine and analyse large datasets, draw valid inferences, and present them to management using specialist software (e.g. Google Analytics for marketing analysts)

Data analyst qualifications

While there are no set qualifications that are absolutely required to become a data analyst, you will stand a better chance with a degree in a computer science, mathematical, or science-based subject. Candidates will be expected to know some programming languages, such as Python or Java, and show strong database design or coding skills.

Because there are no strict learning paths to becoming a data analyst, you have several options to consider to improve your chances of beginning a career in data science.

Level 4 Data Analyst Apprenticeship  

This apprenticeship introduces students to a range of essential skills, from data analysis tools to programming software such as Python and R. During your data analyst apprenticeship, you’ll develop skills across the board that will enable you to generate insights to inform better decision making, which is crucial to any modern business.

Level 6 BSc Digital and Technology Solutions Professional Degree Apprenticeship (DTS)

Ideal for new and existing employees in digital and technology roles, this programme offers a solid foundation for professionals in software engineer, data science, cyber analysis roles, and IT consultancy.

The degree apprenticeship is available in four core specialisms: Software Engineer, Cyber Security, Data Analyst, and IT consultant – therefore on this course, you will select the data analyst pathway. The specialist section of the course takes place in the final year, when you will gain a solid grounding of the detailed technical knowledge required to work as a data analyst.

Level 7 MSc Applied Data Analytics Apprenticeship

The MSc Applied Data Analytics Apprenticeship is aimed at the future stars of data analysis who will tackle real world problems using data science. Upon completion, graduates will be able to  leverage the power of both big data and domain knowledge to generate insights and devise strategies for a range of industry leading organisations.

Data science graduate training schemes

Some employers offer data science graduate training schemes, which typically take two years to complete. Many of these schemes are open to graduates from any discipline, while others specify the degree subjects they will accept.

Skills

As well as excellent numerical and analytical skills, data analysts should possess the following hard and soft skills to thrive in a data science career: 

Machine learning

With AI and predictive analytics at the forefront of data science, a comprehensive understanding of machine learning is a key component of the data analyst’s toolkit. To excel in this area, consider boosting your statistical programming skills.

SQL

SQL, or Structured Query Language, is the ubiquitous industry-standard database language. Regarded by some as a graduated version of Microsoft Excel due to its smooth management of substantial data sets, most modern organisations require an SQL specialist.

Critical thinking

Data analysts uncover and synthesise connections that are not always clear, so the ability to think critically is essential.

Presentation skills

Data analysts are required to generate insights and present their findings in a clear and engaging way to their colleagues or clients. Telling a compelling story with data is also a key aspect of the role, and analysts often employ eye-catching, high-quality graphs and charts to convey their findings effectively.

SEO knowledge

Search engine optimisation (SEO) is the process of improving a website’s visibility on search engines (e.g. Google) for relevant queries. Improved visibility is a key predictor of increased sales, making SEO knowledge crucial (but specifically in marketing analyst roles). 

Salary and benefits

Salaries for junior data analysts tend to start at around £23,000 to £25,000. Graduate schemes in data analysis and business intelligence at larger companies tend to offer a higher starting salary of £25,000 to £30,000, and with a few years' experience, salaries can rise to between £30,000 and £35,000. Experienced, high-level, and consulting jobs can command £60,000 or more.

The benefits for data analysts vary by organisation, but are likely to include a company pension scheme, discretionary bonuses, and private medical insurance. 

Career path

Work experience

Data science internships are available at several major employers, particularly in the media, consulting firms, telecommunications, and the government.  You could also approach small to medium-sized enterprises for internship or shadowing opportunities. Most internships or placements are advertised in the autumn. Bear in mind that with smaller organisations, you may need to make targeted speculative applications.

Is work experience essential?

Many organisations require their entry-level data scientists to have demonstrable work experience before applying. But don’t worry if you haven’t, as any self-directed learning in data analysis or programming will highlight your commitment and enthusiasm for the role.

Data science competitions

Data science competitions represent another option for aspiring data analysts. Used by employers to spot new talent, organisations such as Topcoder and Kaggle host events, while the government backed Data Science Challenge aims to ensure that science and technology contribute to the UK’s defence and security.

Continuing professional development

While there is no official accreditation for working in data science, you will build on your analytical and technical skills as you gain experience in the role. Some major employers offer two-year data science graduate training schemes. In contrast, others provide additional training in their operating procedures or encourage you to attend sector-specific events to help your understanding of potential issues, new developments, or emerging trends.

Find out more about our data and tech programmes here.