Top of the morning to you!
I have been asked many times, “What is the best way to get started in the field of data science?” Well, that first depends on what you want to do and/or what interests you. There is not one particular degree or education that will be an absolute guarantee to the field.
I do not enjoy telling others about what degrees to pursue, as I myself have a very multi-disciplinary background which has been my personal strength in this field. Your background can be your strength, so take pride in it and leverage it to its full potential.
BUT, you will absolutely need to learn the skills to perform the job. There are data professionals with degrees that are in non-technical fields-but they have taken the time to learn the skills that are necessary. So, first take time to think about what you want, what problems you would like to solve, and where you see your career in the long-run. Next, let’s explore what skills are necessary to be a data scientist in 2020.
The skills that are necessary in this field include:
- Programming skills in R and/or Python
- A desire to learn. A natural curiosity. The field is quickly evolving and in order to maintain momentum, you will need to have a desire to continuously learn and grow.
- Knowledge in statistics, calculus and linear algebra.
- As you learn, practice your knowledge on various datasets by building a portfolio. The best way to learn is to practice. Showcase your work.
This will be a time-commitment and likely a long-term endeavor. It will continue well into your career. I am proud to admit that I am constantly learning and sometimes revisiting concepts.
I am not sponsored by any program or person, and these are simply suggestions.
Dataquest has programs that are effective that I enjoy. In order to gain more programming skills, this may be a good start. Coursera and Udemy also has amazing options. I have personally taken several of Jose Portilla’s courses and found them to be excellent.
Get the Job
Practicing your newly acquired skills and building a portfolio will be incredibly useful as you look for work. In the event you are new to the field and do not necessarily have experience, a portfolio with projects in which you can walk the interviewer through, can be a testament to your abilities. Also, having a portfolio with work that you are proud of, will give you a sense of pride, and can help you exude confidence. When applying for roles, focus on the scope of work, the problems that need to be solved-focus less on the title. The title of data scientist sounds super cool, but many folks are working in the field of data science without that specific title.
When applying for work always keep this in mind: companies want to know if and how you can generate value for them. Before interviewing for a role, do research on the company and what generates revenue for them. Pitch a mock project and how you would approach it. Share with them how you will be valuable. This was what I failed to do early in my career, and would ramble about myself longer than I should have.
Lastly, building confidence in yourself will take you far. Feel good about you.
Hope I helped someone out there!