Over the years, data science has become a very hot field for people to enter for many reasons. According to the U.S. Bureau of Labor Statistics, the median salary is over $100,000, with the entry-level education requirement being a bachelor’s degree. Over the next eight years, the field is expected to see a 35% growth in demand for workers so it’s a wonderful field to enter or transition into for both new workers and experienced alike to get your first data science job.
The best part is that there are plenty of opportunities for those with the right skills. But like with any new field, getting your first data science job can be challenging, especially if you’re new to the field.
So let’s go through a few things you can do to improve your chances of landing your dream first data science job.
Focus on the core skills
Data scientists need a strong foundation of core skills divided into sections – hard and soft. Hard skills will include the following to enter the field, the trinity has been constant, and they are Excel, SQL, and Python. These programming skills will help you stand out so that way you can participate and be able to clean and prepare data, and build models.
The second set of foundational skills focuses on soft skills, and this primarily deals with the ability to communicate findings effectively. These skills are less tangible when compared to the harder skills, but they’re just as important. The ability to communicate your data’s story effectively is just as valuable as being able to manipulate data as part of most jobs within data science requires the person to communicate to stakeholders who likely do not share technical skills in the data science world.
Build up a portfolio
This is one of the most important ways of showing off your skills to potential employers. Why? Because in a world full of bootcamps, websites, and other methods of learning data science, it’s becoming more important to show off your ability to utilize your skills. Certificates and degrees are nice, but most often a GitHub repo or even a website with your work will get you much further than a standalone piece of paper (or PDF now).
So what you can do to build up a portfolio of your work? Well, believe it or not, your portfolio could include projects you’ve completed for classes, personal projects, or open-source contributions. Thanks to YouTube, and websites such as Kaggle, there is an unlimited supply of datasets and projects that allow for hands-on experience that can turn into portfolio projects. So make sure you have one that you can be proud of.
This is a big one, and in any industry it’s unavoidable. Networking is a critical way to both get noticed and remembered. You can do this by attending conferences and meetups and connecting with people in the data science community. When people know what you can do, your name will come to mind when they find out about any new opportunity. You can also reach out to data scientists on LinkedIn and ask them for advice or to review your resume.
Brush up on your education
If you still need to become a data scientist, you may consider taking some courses or completing a data science bootcamp to improve your skills. There are also several online resources available, such as MOOCs and online tutorials. You can start slow and steady with free resources online and when you’re ready to commit hard, other professional websites can provide you with the education you need to stand out.
Decide on a niche
Once you have a good foundation in data science, you may want to consider specializing in a particular area. This could be anything from machine learning to natural language processing to business intelligence. Each has its own unique flavors and after exploring the niches, you’ll find the one that best suits your talents. The reason niches are important for the prospective data pro is that they can help you stand out from the competition and make yourself more marketable to potential employers.
As the need to better manage and understand data becomes more important across industries, niches will continue to grow.
One thing you want to get out of this is that getting your first data science job can be challenging, but it’s possible with hard work and dedication. Following the tips above can improve your chances of landing your dream job
Now if you’re interested in learning more about data science, or if you’re looking to supercharge your data science skills, check out the ODSC Ai+ Training platform. Ai+ offers a variety of courses and bootcamps designed to help you get started in the field of data science and later on, continue your data career.