Matt Davies Stockton Explores How to Break into the Data Science Field


According to Matt Davies Stockton, data science is the hottest career in the tech industry. Companies are willing to pay a lot to hire data scientists who can turn binary bits into actionable insights. Let’s figure out how you can break into the lucrative data science field. 

The Details

  1. Figure out what you need to learn – To break into the data science field, you need to figure out the skills that are valued in this field. You may already have some of those skills and need to brush on those that aren’t your strong suit. For instance, you may be a good developer, but lack experience in data visualization. Pick up on the areas you aren’t familiar with and slowly build up your skills in a systematic manner.  
  2. Brush up fundamentals and make math a priority – You may be overwhelmed by the things that you require to learn in this field. However, for entry-level positions, recruiters are more interested in your data science fundamentals. The rest you’ll need to learn at the job. That’s why you need to brush up on fundamentals in data science like SQL, relational databases, distributed computing, and more. 

You’ll also need to focus a lot on your math. It’s a core skill that’s required in data science. You need to be proficient at problem-solving in areas like probability, statistics, and optimization problems. Strengthen your knowledge of correlations and variability. A strong foundation in statistics, calculus, and linear algebra would help you to build neural networks and aid in dimensionality reduction. 

  1. Programming – Programming in data science is quite different compared to general-purpose development. Instead of building software for users, you need to analyze data with programming skills and solve business problems. This kind of programming is heavily dependent on data processing techniques and math intensive. Keep building those skills with sample datasets in R, Python, and other relevant programming languages.     
  2. Data visualization – Data visualization is also very important in data science. Sometimes it highlights patterns in data that go under the radar and also helps you to communicate your insights to less tech-savvy people in the organization. Visualization helps you convey your ideas in an easy and digestible manner. You may start with Power BI and Tableau, two popular data visualization tools. 
  3. Join a Bootcamp and pursue internships – Joining a data science Bootcamp helps you get familiar with the industry and bask in the support of the community. It can accelerate your data science learning journey. Just make sure that the Bootcamp is legit. After you have picked up the necessary skills, you can build your portfolio by joining internship programs at Google and other tech companies. You can also work on your own projects and make your portfolio irresistible to recruiters.  


Matt Davies Stockton suggests that you use the tips mentioned above to break into the data science field. Figure out what you need to learn, brush up on your skills, build strong fundamentals in math and build your portfolio to impress recruiters.