How to become a Data Scientist in 2025

As businesses seek to integrate AI into their workflows, having a competent Data team is increasingly important. What Data careers are there in 2025? How can you join this fascinating field?

Let's dive in.

What is Data Science?

Data Science is a complex discipline that combines Maths, Statistics, Advanced Analytics, Computer Programming, and, increasingly, Artificial Intelligence and Machine Learning, to process business data, uncover insights and trends, and drive informed decision-making.

Data Science is an interesting mix of analytical and big-picture thinking, statistics and storytelling.

What Data careers are there in 2025?

In 2025, Data careers are becoming more complex. 

Interesting Data careers include:

1. Data Engineer
2. Machine Learning Engineer
3. AI Data Analyst
4. Business Analyst
5. Statistician

Adding to this complexity, job titles can vary according to industry and company; for the rest of this blog, let's focus on the umbrella job title of Data Scientist.

What does a Data Scientist do?

As of October 2024, the Internet has around 5.52 billion active users, which, according to the latest estimates, create 402.74 million terabytes of data every day.

Although an average business would only work with a fraction of this amount, it is still overwhelming, complex, and can be contradictory. How can a business understand its figures and make strategic decisions about its growth? This is where Data Scientists become invaluable.

Working alone or as part of a team, Data Scientists use their statistical and programming skills to analyse huge amounts of data from various sources and create insights that management can use in their decision-making process. 

• Identify relevant data sources
• Collect, integrate, and preprocess structured and unstructured data
• Devise algorithms and models to mine data; experiment to find the most efficient analytical methods
• Test, clean, and validate data
• Work with Software Developers and ML Engineers to automate processes and build predictive models
• Combine data models through ensemble modeling
• Analyse data to uncover trends and patterns
• Present insights using data visualization techniques

How much does a Data Scientist make?

In 2024, Data Scientist salaries start at £30,000, with experienced Data Scientists making more than £80,000.

Data Scientists can also work as consultants with varying rates.

What skills do you need to become a Data Scientist?

Data Scientist is a complex role—you need to be able to work with data, understand it, and help other colleagues, who may not be as technical, understand it too. 

To become a Data Scientist, you must be able to:

1. Communicate with colleagues from different teams, often people who do not have a technical background.

To process data, you need to understand how that data will be used and what kind of insights your team is looking for. What do they want to do? What kind of strategy will your insights be used to inform? Having a big-picture view of these parameters will help you in your role greatly. 

2. Be a team player. 

It sounds trite, but the more complex the industry you work for and the bigger your company, the more you will need to create strong connections with peers. These will help you cut through the jargon and solve problems faster.

3. Analyse data.

As you would expect from a technical role, you need advanced skills in Mathematics, Statistics, Algebra, Probability, Calculus, and other specialised areas. Everyone has weak spots, however; do not get discouraged if you're not a math whiz. This role is about tech, but also big-picture thinking, and Data Science tools are becoming increasingly user-friendly. 

3. Process data with software.

For this, you need to be competent in at least one coding language such as Python, R, SQL/MySQL, or C/C++ Find the programming language that appeals most to you and learn it; others will become easier to understand. If you'd like to go into a particular industry, research the programming languages it uses and focus on those.

4. Visualise data.

To create insights, you need to pull the data into visualization software such as Tableau, Qlik Sense, Zoho, Microsoft Power BI, Matplottlib, or d3.js; this software will help you develop insights that you can then present to your team.

5. Tell a story.

Once you know that your findings are accurate, depending on your job role, you may need to present them in an engaging way to the wider team and stakeholders. Going back to points 1 and 2, communicate with your team to understand the kind of insights they're looking for and use software—from the humble PowerPoint to Flow Immersive, Flourish, or Tableau Story Points—to explain your findings.