Hiring a Business Analyst vs. Data Scientist: what you need to know

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In today’s digital world, data is king when it comes to understanding and improving business performance.

As a result, businesses of all sizes in industries such as IT, banking, fintech and accounting are investing in two key data-centric roles, Business Analyst and Data Scientist.

While on the surface these roles are similar, their objectives and skill-sets are distinct, so it helps to know the differences when deciding which one to hire.

If you want to understand the differences between a Business Analyst vs. Data Scientist, read on to learn more and determine which one is the right fit for your organisation.

What is a Business Analyst?

Business Analysts help to improve business performance by analysing data, creating reports, and making recommendations to stakeholders. This role often bridges the gap between finance and technology, using data to understand performance against KPIs and uncover opportunities for increased efficiency.

The daily role of a Business Analyst involves a mix of technical and soft skills. Their technical tasks include using software to analyse figures and statistics and monitor market trends, while interpersonal skills are required to build client and stakeholder relationships and conduct meetings to discuss the Business Analyst’s recommendations.

What is a Data Scientist?

Data Scientists manipulate large amounts of data to create models that guide and inform business strategy. They work with structured data such as consumer or supply chain information, and unstructured data, which is often text-based and may be pooled from multiple sources into a ‘data lake’. A Data Scientist is able to model this unstructured data and identify trends and patterns that could improve organisational performance.

Data Scientists use programming skills to turn raw data into insights and write machine learning algorithms to predict future trends. They spend most of their time working on high level strategic priorities.

What are the differences between a Business Analyst vs. Data Scientist?

Business Analysts and Data Scientists both work with big data, but these roles are fundamentally different.

In addition to being skilled at data analysis, Business Analysts are commercially minded. They are strong communicators, able to craft compelling reports and deliver presentations to clients and stakeholders. People in this role may come from a management or business development background.

In contrast, a Data Scientist is a specialist in data, not necessarily in commerce. They help companies understand data and how it should be incorporated into their strategies. Data Scientists usually have coding skills and a background in computer science or statistics.

These roles have similar average salary ranges, but a Business Analyst typically earns slightly more due to greater demand and the role’s hybrid function.

Related: Not sure how you should be paying for a Business Analyst vs Data Scientist? Visit the Robert Half Salary Guide to find out more.

What is driving demand for these roles today in Australia?

During the pandemic, there was rapid growth in global data capture as people spent more time at home using smartphones and computers.

Today, data-centric roles such as Business Analysts and Data Scientists are experiencing strong growth as companies seek to increase their capabilities in a data-driven business landscape.

As extended border closures have reduced the amount of international talent hitting Australian shores, the best candidates are in hot demand and are usually snapped up quickly.

So, what should you look for when hiring a Data Scientist vs. Business Analyst? Let’s take a look.

Skills, experience and qualifications to look for when hiring a Data Scientist

Here are some of the skills and experience to look for when hiring a Data Scientist:

Skills in programming languages like R, Python, SAS and SQL
Data visualisation skills and knowledge of tools such as Tableau, Sisense, Google Data Studio
Creating and applying mathematical models
Ability to solve complex problems
Creating machine learning algorithms

A Data Scientist will have a degree in data science, computer science or mathematics. They may also hold certifications from industry vendors such as IBM, SAS and Microsoft.

Skills, experience and qualifications to look for when hiring a Business Analyst

Here are some of the key skills and experience to look for when hiring a Business Analyst:

Skills in Excel and other spreadsheet software
Excellent communication
Commercial acumen
Data visualisation skills and knowledge of tools such as Tableau, Sisense, Google Data Studio
Experience creating reports and presentations

A Business Analyst usually has a degree in commerce, business management, or IT.

Need help hiring for either of these roles?

If you’re still unsure whether a Business Analyst vs. Data Scientist is right for your organisation, we can help you make the right choice, and our expert team will connect you to the best candidates to support your company’s continued success.

Get in touch today to learn more about how we can help you.