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Data analyst vs data scientist – differences explained

A split screen of two people working on computers with data

Data analyst, data scientist – tomayto, tomahto, right? It’s easy to make the mistake of thinking these job titles are interchangeable. But although both roles are often mentioned in the same breath, there are significant differences. So let’s dig into what each job involves, the salary, the likely career path – and which role could be right for you.

What’s the difference between a data analyst and a data scientist?

Data analysts find answers to given questions. Things like: did our ad campaign reach our target audience? Or, what behaviours are associated with good heart health? To do this, they typically work with tools such as Excel, SQL, R, Python, Tableau, and Power BI – using them to collect and organise data, and look for patterns and trends. This is where the magic happens. Data analysts can discover insights that would otherwise be lost in the mass of information. Then they present their findings in easy-to-understand reports to help organisations make better-informed decisions.

Data scientists may have experience as a data analyst, but with added coding, software engineering skills and working with much larger and more complex data sets. They will work out what data to collect in the first place, and how to collect it. They do this by creating complex mathematical models and writing algorithms. Data scientists use techniques such as machine learning and artificial intelligence to make predictions and forecast future patterns.

What are the differences in pay between these roles?

In the United Kingdom, the national average salary* for an experienced data analyst is £62,000. For a data scientist, it’s £70,000.

Career path for a data analyst

At an entry level, your main duties are likely to centre on reporting and creating dashboards. To progress to senior data analyst, you’ll need to show strong tech knowledge and good interpersonal skills as the role is often a balance between hands-on data collection and analysis, and mentoring junior employees. As you gain experience, you could take on a leadership position as an analytics manager. Then move up to become director of analytics, or chief data officer.

No matter what your level, your skills will be transferable to a huge variety of industries, so you could move between different sectors or go into academic research and teaching. There’s also the option to work as a freelance consultant.

Career path for a data scientist

You could specialise in one area such as artificial intelligence, machine learning or database management. Then, as you step up to more senior roles, you could take on responsibility for people or project management. Lead and chief data scientists will evaluate emerging technologies, and shape their organisation’s data science strategy by creating new systems and processes. They may take on an outward-looking role and represent their company at events and conferences. Or build and develop relationships with clients.

Are data analysts and data scientists in demand?

The current digital skills gap means there are more vacancies for data analysts and data scientists than qualified professionals to fill them. As a result, many organisations are turning to data apprenticeship programmes to train up new-starters and career-changers, as well as their current employees.

How do I get my foot in the door?

Kaplan is a tried and trusted apprenticeship programme provider with a wide range of data apprenticeships. Our Data User Apprenticeship Level 3 is a good starting point if you are new to the world of data. Or you could jump in at our Data Analyst Apprenticeship Level 4. This would suit you if you’re looking to broaden your knowledge and develop skills in Power BI or Tableau tools.

For anyone looking to move from data analysis to data science, the good news is you can use Kaplan’s apprenticeship programmes as a stepping stone to progress to a Level 6 Data Scientist Apprenticeship, which is an integrated degree apprenticeship.

In today’s digital-first world, there’s never been a better time to embark on a career in data. Now you know more about the differences behind the two roles, take a look at our range of data analytics courses and programmes to see how Kaplan can help you get started.

* Figures from nationalcareers.service.gov.uk, August 2022

Kickstart your career in data with a level 3 apprenticeship

Learn more

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Data analyst vs data scientist – differences explained

A split screen of two people working on computers with data

Data analyst, data scientist – tomayto, tomahto, right? It’s easy to make the mistake of thinking these job titles are interchangeable. But although both roles are often mentioned in the same breath, there are significant differences. So let’s dig into what each job involves, the salary, the likely career path – and which role could be right for you.

What’s the difference between a data analyst and a data scientist?

Data analysts find answers to given questions. Things like: did our ad campaign reach our target audience? Or, what behaviours are associated with good heart health? To do this, they typically work with tools such as Excel, SQL, R, Python, Tableau, and Power BI – using them to collect and organise data, and look for patterns and trends. This is where the magic happens. Data analysts can discover insights that would otherwise be lost in the mass of information. Then they present their findings in easy-to-understand reports to help organisations make better-informed decisions.

Data scientists may have experience as a data analyst, but with added coding, software engineering skills and working with much larger and more complex data sets. They will work out what data to collect in the first place, and how to collect it. They do this by creating complex mathematical models and writing algorithms. Data scientists use techniques such as machine learning and artificial intelligence to make predictions and forecast future patterns.

What are the differences in pay between these roles?

In the United Kingdom, the national average salary* for an experienced data analyst is £62,000. For a data scientist, it’s £70,000.

Career path for a data analyst

At an entry level, your main duties are likely to centre on reporting and creating dashboards. To progress to senior data analyst, you’ll need to show strong tech knowledge and good interpersonal skills as the role is often a balance between hands-on data collection and analysis, and mentoring junior employees. As you gain experience, you could take on a leadership position as an analytics manager. Then move up to become director of analytics, or chief data officer.

No matter what your level, your skills will be transferable to a huge variety of industries, so you could move between different sectors or go into academic research and teaching. There’s also the option to work as a freelance consultant.

Career path for a data scientist

You could specialise in one area such as artificial intelligence, machine learning or database management. Then, as you step up to more senior roles, you could take on responsibility for people or project management. Lead and chief data scientists will evaluate emerging technologies, and shape their organisation’s data science strategy by creating new systems and processes. They may take on an outward-looking role and represent their company at events and conferences. Or build and develop relationships with clients.

Are data analysts and data scientists in demand?

The current digital skills gap means there are more vacancies for data analysts and data scientists than qualified professionals to fill them. As a result, many organisations are turning to data apprenticeship programmes to train up new-starters and career-changers, as well as their current employees.

How do I get my foot in the door?

Kaplan is a tried and trusted apprenticeship programme provider with a wide range of data apprenticeships. Our Data User Apprenticeship Level 3 is a good starting point if you are new to the world of data. Or you could jump in at our Data Analyst Apprenticeship Level 4. This would suit you if you’re looking to broaden your knowledge and develop skills in Power BI or Tableau tools.

For anyone looking to move from data analysis to data science, the good news is you can use Kaplan’s apprenticeship programmes as a stepping stone to progress to a Level 6 Data Scientist Apprenticeship, which is an integrated degree apprenticeship.

In today’s digital-first world, there’s never been a better time to embark on a career in data. Now you know more about the differences behind the two roles, take a look at our range of data analytics courses and programmes to see how Kaplan can help you get started.

* Figures from nationalcareers.service.gov.uk, August 2022

Kickstart your career in data with a level 3 apprenticeship

Learn more

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