Top skills needed in Data Science careers
In the past decade, there has been a major shift in the demand for data science careers. In 2020, the median salary for data scientists was over $122k, according to the Bureau of Labor & Statistics, and the BLS expects this demand to continue to rise for a long time. As you consider how you will get started with your data science career, there are several skills you need to hone in order to compete in the workforce.
Before we get into the necessary skills you need for data science careers, let’s talk about two important aspects when applying for these kinds of jobs:
First, it is important to define the difference between “data scientist” and other related positions. A data science career can often be titled something similar like “data analyst” or “machine learning engineer”, so you want to make sure you are looking at all types of these positions when conducting your job search. Often, searching by keyword or job skills is more important than searching than a specific job title.
Second, you need to be able to considering how you will present your portfolio of work in an interview. It is one thing to write on your resume that you have data science skills, but it is another step altogether to be able to back that up with experience and real-world application of your skills. You will want to build up a showcase of projects that you can quickly and confidently show to an employer, and also expect that you will be quizzed heavily on the experiences on the job, working with clients, and related.
Be prepared for your interviews with a combination of school projects, independent work, or, better yet, contract or freelance work you may have landed. Your GitHub link should be included with your resume and up to date as well.
Now, that you know what to expect during the application process, let’s consider the top skills you need to really land that dream data science job.
Data Science Programming
Data Science is a unique combination of statistics, programming, modeling, and more. If you want to work in data science, there is no avoiding that you have to be a strong programmer. The two most common languages used in this field are Python and R language. Both are useful, but it will depend on your goals: Python has grown to become more popular in the business world, while R is still very popular in the research and academic worlds. Python is considered to be more versatile today but may not always be directly related to data science careers, while R is focused on working with data and performing statistical analysis and less flexible.
Digital Workshop Center, we focus on Python in our data science bootcamp because we are trying to best prepare our students for work in the business world more than anything else. It would be wise to be familiar with both in the end.
Once you decide on a language to focus on, there are also general programming skills you should be consistently improving. Simple understanding of code flow and logic structures are applicable in many areas of programming, and the more you can learn there, the better. Other tools like Git and GitHub are absolutely essential today and you must have these confidently shown on you resume as well. Understanding of tools like UNIX command line (sometimes called terminal, bash, etc) can help you work more efficiently while command line skills in general can help when working with cloud data. These would be valuable team tools for any job you may land.
In order to develop your Python skills, you have a wide variety of education options. From simple YouTube videos to a full length program like our data science bootcamp, it is most important for you to find the right education option that fits your learning style. When it comes to coding, it is most important that you are learning by doing. It is not the same to watch someone code in a video versus doing it yourself and achieving the proper results. Hands-on and mentored learning is our focus at Digital Workshop Center, and we feel this is the best way for adults to learn new programming skills.
Once you have your programming skills ready to show off in your portfolio, it is very important that you add these skills to your resume and include your GitHub link to recent projects. Your programming skills are likely to be tested in an interview, so prepare for both verbal and written tests, an on-site project, or take-home project.
As you explore data science careers, you will inevitably come across the need to know SQL or Structured Query Language. SQL is essential because it allows you to retrieve and filter information from a database. SQL is often overlooked by young programmers, but it is just as important as the programming when it comes to data science.
There are also a wide range of learning options for SQL. Mode Analytics has a free SQL tutorial that is popular and doesn’t require any prior experience. Again, be sure to include some mention of SQL on your resume and a demonstration of these skills in your GitHub when possible. Expect to be quizzed on some SQL basics in an interview, and you could even have to sketch an SQL query on a whiteboard.
And speaking of soft skills, you also need to make sure your business soft skills are just as honed as your tech skills. Important soft skills for working on a technology team include professional communication, business writing, leadership, and time management. The importance of business soft skills boils down to this idea: it is important to be able create complex visualizations, but even more important to be able to explain them to your colleagues.
Some of your team members may not understand a data visualization graph, but everyone can understand a bar graph. Design skills in these areas can go a long way to help you communicate your findings and highlight the important parts of what you are trying to communicate with data.
Written and spoken communication skills are just as important. Being able to effectively present or manage a team will put you in a better position to grow within data science careers. And, expect to work with others in technical and non-technical roles, so you need to be versatile in how you approach different people with a wide range of skill levels. Consider taking a business soft skills workshop if you feel that you need to improve in these areas and become a better team member in the end.
For all of these above skills, it is important to balance having the skills and clearly demonstrating on a resume. Your projects will be key to getting those interviews; and those interviews will challenge you with various kinds of demonstration of your skills on the spot. As data science careers continue to grow, you will want to stay on top of the latest trends in the industry. The most important thing is to get started with your education and down the path to an exciting new data science career today.
If you have questions on the Data Science Bootcamp at Digital Workshop Center, you can always talk to a student advisor for free. Good luck with your job search!