What does a data analyst do?

Data analysts use large amounts of data to understand your business and suggest improvements to streamline your operations. They typically receive guidance from your company’s leadership team.

Data analysts spot trends using structured historical data to help improve processes. They often use SQL commands to find related data.

After collecting relevant data, a data analyst formats and organizes it to ensure its accuracy and relevance. Then, they analyze the data using various tools and techniques, such as statistical analysis and predictive modeling.

Once they’ve analyzed the data, they simplify it for collaborators through reports and visual representations. They may also recommend actions based on the data.

What does a data scientist do?

Instead of starting with a specific question or problem, a data scientist typically explores available data to discover relationships between concepts and questions you haven’t thought to ask. Their work is technical and involves using advanced data techniques.

Data scientists gather data from various sources, including structured and unstructured data. They perform their duties using their programming skills. Their methods may include creating machine learning (ML) algorithms and predictive models.

Working with a data scientist could help you resolve issues before you realize they exist. You might also gain a competitive advantage by learning about opportunities and improvements before others in your industry discover them.

Differences between a data analyst vs. a data scientist

Data science and analytics vary in several ways, even though both roles manage large amounts of data. The following are common differences between data science vs. data analytics.

Average pay rates

A data scientist makes an average of $123,273 per year, according to Indeed Salaries. The pay rate for a data analyst averages $80,032 per year. This discrepancy accounts for the more advanced data techniques data scientists typically use.

The cost of hiring is often a major consideration for companies. Hiring a data analyst may be a more affordable option. However, before hiring an analyst instead of a scientist for monetary reasons, consider whether a data analyst can provide the support you need.

Job requirements

Jobs for data scientists typically have more requirements for candidates because of the advanced duties. However, you might consider hiring based on skills and experience rather than degrees.

Skills

Candidates for both roles need to know how to handle data and have a solid foundation in math and statistics. Additional skills vary, with data analysts needing strong data visualization abilities. Analysts should also know how to use SAS and Excel proficiently and understand programming languages, including SQL and Python.

Data scientists often need advanced statistics and object-oriented programming skills. Experience in machine learning (ML) and data modeling is also important. They may also use tools such as Hadoop, Spark and MySQL.

Primary focus

Data analysts aim to resolve problems you already know your organization has to improve outcomes.

However, data scientists search for data and patterns to reveal unknown issues or opportunities that could advance your business.

Type of analytics

Data analysts most often use descriptive analytics, which pulls historical data to track patterns and understand why something occurs.

Data scientists use descriptive, predictive and prescriptive analytics. Predictive means forecasting expected events based on previous data trends. Prescriptive combines findings from descriptive and predictive analytics to advise the company on potential changes.

Which role you need to hire: Data science vs. data analytics

Since both roles help you manage large volumes of data, you may be unsure which may help you most. Looking at the differences in a data analyst vs. data scientist may be easier when focusing on these areas:

• Purpose or goal: Do you have specific issues you want to resolve, or are you looking for help improving your company overall? Data analysts find answers to questions you already have, while data scientists search for new questions to consider.
• Budget: Calculate how much you can afford to pay your new hire. Data scientists may require a higher budget than data analysts.
• Skills: The level of a candidate’s skills often depends on the role, with data scientists typically having more in-depth knowledge.
• Data sources: When you want a broader source of structured and unstructured data, a data scientist can perform those duties.
• Current team makeup: If you already employ a data scientist or a data analyst, you might consider hiring the other to diversify your team.

When you should hire a data scientist

Companies might consider hiring a data scientist to help with these circumstances:

• You want predictions about what could happen with your business or industry.
• You want to use advanced technology, such as ML and AI.
• You want a data expert to break down complex information for all collaborators.
• You want a professional to help drive your business decisions.
• You want to use data from a range of sources.
• You prefer someone with a strong technical background with advanced programming skills.
• You already have a data analyst on staff.

When you should hire a data analyst

Hiring a data analyst could benefit your company in these situations:

• You want to resolve various challenges.
• You want to focus on existing data.
• You want actionable insights.
• You already have a data scientist on staff.

Frequently asked questions about data science and analytics

Can a data analyst do the job of a data scientist?

The job of a data scientist is typically more advanced than a data analyst. However, a data analyst with experience and a background in data science and analytics might handle the duties of both roles.

The quality of the data information you receive is important, so assess whether the data analyst can perform data science tasks. With high-quality data, you can make more effective business decisions.

Does a company need a data scientist and a data analyst?

Data analysts and data scientists offer different data-based business support, so you could have both roles within your company. Smaller organizations might select one based on the workload. A larger organization may hire both roles or employ multiple data scientists or data analysts.

How do you hire a data analyst?

Create a detailed job description to attract candidates who fit your needs. Develop data analyst interview questions to ensure a fair hiring process. Consider candidates with a degree in computer science, statistics or a similar major, or opt for skills-first hiring by selecting candidates whose abilities align with the role.

It may also be beneficial to interview candidates who have experience with programming languages, data visualization tools and descriptive analytics.

How do you hire a data scientist?

Tailor your data scientist interview questions to the specific duties of your role, such as gathering raw data, cleaning data and developing ML algorithms. Candidates with advanced degrees or extensive experience may be more suitable for your organization. Ask candidates to take assessments to evaluate their programming, ML, math and big data knowledge. If you already have a data analyst on your team with extensive experience, you may consider moving them into a data scientist role.