Top Data Science Skills To Learn In 2023

One of the funny realities of life is the fact that the beginning of a new year brings new goals, challenges, and aspirations. Some are mainly personal, but others involve an organization. All these new goals can sway an industry and send some people off their career paths. To ensure that you stay in line with your data science career, you need to develop new valuable skills and update old ones. 

In this article, we have highlighted the top 10 skills that you should consider learning to position yourself for a data science career growth, especially in the rapidly changing technology space.

Upskill Yourself in 2023 with these 10 Data Science Skills.

Here we go… 

  1. Data Analysis

According to the Accenture Human Impact Data Literacy report, only 27% of organizations were able to make full use of their data to generate actionable and viable insights in 2019. The number of organizations have grown immensely but the need is not completely filled. The companies surveyed mentioned that the growing gap in data science and analytics skills is the major cause of this challenge. 

To position yourself for success in 2023, you should consider improving your data analysis skills. This involves mastering the use of analytic tools, including Tableau, Excel, and Jira among others. By simply mastering these tools, you will be able to find your place in the huge data science skills gap and work with some of the most prestigious organizations. 

  1. Machine Learning

Leading companies, such as Google, Facebook, and Uber, make Machine Learning a central part of their operations. They collect a humongous amount of data and have these machines process and analyze them in real-time. This way, they can monitor trends and predict future market changes even before they happen. 

Machine Learning has become less expensive over the years and is accessible to small and growing businesses too. So, it’s no longer a tool for the big guns only. You can improve your machine learning skills to offer more value to clients in 2023.

  1. Data Intuition

In business, real life, and even throughout your data science career, there is never enough data to make an infallible decision. You need to be able to make quick decisions or gain a substantial understanding of a situation with limited data. This is what data intuition means. 

To advance your career in 2023, you should consider improving your data intuition. This will save you a lot of time and effort. By simply taking a glance at certain distributions, you can easily tell what your next actions should be. 

Interestingly, your data intuition improves as you expose yourself to more data. However, you can fast-track your intuition qualitatively by taking a hobby in solving data science puzzles. 

Here’s an HBR article on how data intuition plays a big role in your career advancement, especially when dealing with big data. 

  1. Natural Language Processing

Although NLP has been around for a while, there is an unfilled gap in the skills required to make machines interact seamlessly with humans. In the next few years, the software will be designed to understand human language better. This may go beyond voice recognition and language processing. 

AI tools may dive deeper into understanding unspoken languages, including tone of voice, speech patterns, and even body language. New virtual assistant software is being developed and existing ones are advancing. Improving your NLP skills can greatly position you to thrive in the coming years.

  1. Business Intelligence

Running a business comes with a lot of guesswork. How will customers respond to your next feature release? What could work between two product ideas? And so many other causes of uncertainty.

Business Intelligence removes the guesswork from running a business. You can collect data to understand what works within an industry and help these businesses make better data-driven decisions. By learning how to use the top BI tools, you can stand out and offer more value to your clients in 2023. 

  1. Data Visualization

Data is one insanely difficult thing to communicate. It’s all numbers until someone comes around to make sense of it. For growing businesses, having access to data is not the issue. Making sense of the data is. And with the right data science skills in 2023, you can be the guy that helps businesses make good sense of data by helping them visualize it. 

Currently, there are dozens of data visualization tools that you can learn. However, we strongly recommend that you take up Tableau courses, given that it’s one of the most used visualization tools at this time. Grafana and Google Charts are also very useful tools to master. 

  1. Communication and data storytelling

Whether raw or visualized, data is just numbers and charts. People need to build a personal connection with the underlying situations that generated those data. Also, they need to have a holistic understanding of the data before them.

What this means is that businesses (especially executives) will gain better insight and see the true significance of data if you can translate the data into a relatable story. With such data storytelling skill, you can transform data from abstract numbers and charts into real, imaginable cases.

Given that data storytelling is one of the most powerful skills to have as a data scientist, you should consider placing it on top of your upskilling goals for 2023. 

  1. Python & R

According to the Stack Overflow Developers survey, SQL and Python are the third and fourth most popular technologies, respectively, among professional developers.

Although the R technology is a more specified tool, Python is a general-purpose language used for a variety of cases. Believe it or not, Python and R are the most used languages when it comes to Machine Learning and other data-related fields.

Focusing on Python, it has a broad spectrum application and is considered a recession-proof technical skill. So, whether there’s a drought or flood in the job market, the expertise of a good Python developer will be needed. 

Bundled with R, you can become an “Enterprise Data Scientist” needed by some of the highest-ranking companies.

You can start your journey by taking these Python Skill Track. And also complement it with the R For Data Science Skill Track

  1. SQL

Let’s not forget the basics. SQL is, and will remain, a very vital skill to perfect even in 2023. Basically, all of data science is rooted in the SQL principles. You may not be required to work directly from databases but an understanding of the database connection through SQL can help you diagnose serious data access issues and cut out the need for an engineer every time. 

While Python is a versatile language for developers, SQL has been classified as a more resourceful language for data science professionals. It ranks above Python and just beneath HTML in the StackOverflow developers survey. 

  1. Soft skills

Yes, technical skills are a big deal. However, having the right soft skills can set you up for massive success in your career. 89% of HR professionals posit that the lack of soft skills is the reason why most hires don’t work out, despite these candidates having strong technical expertise. 

So, while you develop more technical skills to supercharge your career in 2023, you should pay some attention to your soft, non-technical skills. On top of those skills to improve are effective written communication (given that teams often communicate via emails and channels like Slack), leadership (even though you’re not leading a team yet), teamwork, and emotional intelligence. There are a few others to consider working on, but these four can get you started big time. 


Data science, as a field of study, has been around for quite some time. Albeit, it is still a new career path, especially in the business world. As with every new path, there is a lot of volatility within the industry, which is an exciting experience.

To make it through the changing tides, you need to acquire the right skills and master them. And the right skills are relative to the industry landscape at every given moment. So far, we are very confident that these ten skills discussed in this article will be at the center stage of the data science industry in 2023. You should do well to acquire them. 

We are regularly updating our readers with insightful takes on data science-related topics. You should consider signing up here at SDS Club or checking out the DMC Community to avoid missing out!


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