Key Data Scientists Skills Needed in 2023 and Beyond
The field of data science is an exciting and enticing career. Increasingly, the use of data and its management are leveraged day in and day out across a range of industries, and as such, data science isn’t just a career of today but one with longevity.
Data scientists’ skills constantly evolve and a career in this field requires continuous training to keep pace with change. In this article, we look at the key skills needed to be an effective data scientist now and in the future.
Programming
All data scientists need to be able to program computers to manage unstructured data sets. This underpins much of the statistical analysis needed by data scientists. Python is the most common computer language data scientists use and many learn data science with Python to get ahead of the competition.
Other programming languages include Perl, C/C++, SQL, and Java.
Analytical Tool Proficiency
Another key skill to learn as a data scientist is to learn how to use analytical tools. Data scientists extract valuable information from structured data as part of their job. They look for trends that emerge and present them to industry.
There are a few analytical tools on the market. SAS, Hadoop, Spark, Hive, Pig, and R are the most common and certifications can be earned in each of these tools which allows you to show competency to future employers.
Unstructured Data Management and Research
A key challenge for data scientists is to take information from different sources and determine if there are commonalities between them. For example, a project may require you to look at data obtained through artificial intelligence, machine learning, social media, statistics, and probability may play a part as well. All of this data has to be sifted and quantified so analysis can be done.
Data scientists earn their money!
Business Know-how
A good skill for a data scientist to have is business know-how or acumen. Having an overview of why the data needs to be managed and structured helps focus your efforts and gives you a better idea of what trends to look for. It also helps when presenting findings to a review panel or team. Often, the data is complicated to understand, but being able to anchor it in the business will help those you report to grasp the concepts and make the whole process smoother and easier to understand.
Communication
All jobs require some level of communication so the better you can convey ideas and concepts to coworkers the better. As a data scientist, you will be part of a team and all team members will have a specific job to perform. You’ll have managers to report to who will coordinate the team as needed for the project. As such, being able to communicate well with your coworkers is essential for the success of the project.
If you feel you have the acumen for data science it is a good idea to start to learn to program as computer modelling is essential together with strong analytical skills.
Good luck with your computer science endeavors.