So You Want to Be a Data Scientist? Here’s How to Get Started
Do you dream of becoming a data scientist? Are you currently working toward that goal? If the answer to either of these questions is yes, then this article is for you. Here are some practical tips on how to become a data scientist—and fast! You can do it if you put your mind to it! You’re going to be data scientist-ing in no time!
Figure out what kind of data scientist you want to be
Data scientists come in many different forms: data engineers, data analysts, machine learning specialists, business intelligence analysts. And all of them have their own skills and requirements for how to become a data scientist. Data engineers are the ones who actually collect the data and maintain databases. Analysts use their knowledge of statistics and machine learning to extract insights from it. Machine-learning specialists design predictive models that identify patterns in datasets with the goal of understanding how these patterns will evolve over time. Business intelligence analysts design dashboards and reports for executives to help them make better decisions about what direction the company should go in.
Learn the basics of coding and statistics
Becoming a data scientist requires you to learn how to code, as well as statistics. It is best if you start with the basics, and work your way up. Learn how to code using Python or R. Once you feel comfortable enough with coding, move on to statistics. There are many books out there that teach both coding and statistics at the same time. It is also important that you know how to use SQL, as most of the data scientists in today’s world use SQL for querying databases and manipulating data sets for analysis.
Find a mentor in the field
One of the best ways to learn how to become a data scientist is by finding an experienced mentor in your area and asking them for help. A mentor can help you find the right classes, books, and places where you can get hands-on experience. Mentors are usually more than happy to answer any questions that you might have. Mentoring relationships vary from person to person, so make sure that the one you choose will be able to teach what you want to know.
Start building your portfolio
Building your portfolio is important if you want to get into data science. As with any industry, the more experience you can show off, the better. But how do you go about getting that first project? And how do you know where to look for jobs in the first place?
First, make sure you have an updated resume and cover letter. Next, look for opportunities on LinkedIn by checking out other people’s profiles (you can also search for companies and see who they are hiring).
*After that, it’s time to start applying. Many companies will ask for a cover letter and resume before moving forward with the interview process. To write an effective cover letter, think about what the company does and how you might be able to help them meet their goals. Keep it concise – 3-4 sentences max – and include things like your previous experience, skillsets, work style, etc. Once you’ve found a position that interests you but isn’t quite right for whatever reason, reach out to the company and let them know why you’re interested! There’s nothing wrong with following up every once in awhile because most employers appreciate being reminded of how great of a candidate you are.
Stay up-to-date on the latest trends
A data scientist is someone who is skilled in statistics and computer science. They use their expertise to create predictive models that help companies make better decisions. Data scientists must have strong math, analytics, and coding skills. The best way to learn how to become a data scientist is by taking courses or working with experts in the field. If you’re not sure where you want your career path to lead yet, consider majoring in computer science or statistics. A data-science related degree will prepare you for the future of work and give you an advantage over those who don’t have the skills necessary for this exciting position!