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5 Technical Skills That Will Get You Better Data Science Opportunities
How I improved my career with simple skills
I’ve wasted a lot of years in the Data Science industry. From chasing jobs with no room for improvements to trying to be everywhere in the industry — one way or the other, I have made costly mistakes.
Who hasn’t? The important thing is getting back up after the setback.
With the success I’ve gotten now, the biggest regret in my Data Science career is not acquiring enough technical skills. After getting a job at one of the top companies in finance, I relaxed and spent time partying and chilling with friends.
Nothing wrong with leisure but if I had channeled that energy into developing myself, I probably would have gotten my dream mentorship with Frank Andrade.
In today’s world, the demand for data scientists is on the high rise which makes the discipline present a captivating career path for students, amateurs, and computer science professionals.
The U.S. Bureau of Labor Statistics predicts that the Data Science field will grow by about 28% through 2026. Massive.
Typically, Data Science is bound to create more job opportunities basically anywhere information transmission is carried out frequently.
All data scientists must consider that technical skills are just as essential for progressing to the next level.
1. Math & Linear Algebra.
Yes, Math. That same subject you faked an illness to get out of in seventh grade. Math remains an integral part of Data Science, however, there have been controversies around the usefulness of Math in the entire Data Science industry.
So here’s the deal. Some people think Math is only necessary for some parts of the industry.
They agree that Math is only necessary for Data Engineering, Advanced programming, Artificial intelligence, and Business intelligence. While some other groups of people are supporting the motion that every professional in any Data Science field must have a solid foundation in Mathematics.
