Disclaimer: This story is not to discourage you from. Rather, it is a long side can view their own mirror.
So you are very enthusiastic scientific data, you have read dozens of blog posts done some online courses. Now you dream about it as your career. After all, according to the "Harvard Business Review," she said this is the sexiest job of the 21st century.
However, although you are very passionate, scientific data may not be suitable for you. At this moment, you hold too much fantasy and false stereotypes.
Now, your task is simple:! Remove those things hinder your progress you will be surprised of the speed of their advance.
Do you think your degree is enough
You have a master's degree in related field, or even a doctorate. Now you want to step ahead in the field of data science.
But you used the Shell program before? When you happen to find an error, you feel the threat from the command line interface? Have you ever used the tb-class large-scale databases?
If you answered yes to either of these questions is no way, it means that you are not ready. You need some experience and build some actual projects. Only then can you experience problems as the data scientists encounter every day. Only then can you develop problem-solving skills.
Then congratulations you get your degree. Work will now begin.
Your lack of enthusiasm
Have you ever put the whole weekend into a geek project? Have you ever been out with friends at a party browser GitHub night? Have you ever programming because you prefer your favorite hobby say no?
If the above questions you can not answer "yes", it means you have enough passion. Data science is about to face the really difficult problems to solve and stick them until you find a solution. If you do not have enough passion, you will retreat in the face of a difficult first.
Think about what attracted you to become a data scientist. It is a charming title? Or is looking for insights in vast amounts of data in the foreground? If the latter, you are heading in the right direction.
Without passion, there would be no success.
You are not crazy enough
Only crazy idea is a good idea. As a data scientist, you need a lot of data. You just need to keep an open mind on the unexpected results - they often happen!
But you also have to find solutions to the really difficult question. This requires an extraordinary level, you can not complete your normal idea.
If you are always told you insane, it means you are heading in the right direction. If not, you need to change your madness.
Of course, this requires some courage. Once you expose your odd behavior, some people will be scratching his head, his back to you. (Reject you)
But it is worth it. Because you are true to yourself. You lit the spark as a data scientist needs.
You learn from a textbook and online course
Do not get me wrong. Textbooks and online courses are a good way to start. But only the beginning!
You need to invest as soon as possible to a real project. Of course, if you can not write a line of code in Python, then the Python build the project does not make sense. But once you have established a modest basis, we must actively together.
Learning by doing is the key.
GitHub start building your personal home page. Hackathons and Kaggle participate in some competitions. Some blog and write about your experience.
Everyone can use textbooks. To become a data scientist, you must do more.
Do you think you can stop learning at some point
You have subscribed to a number of scientific data about the online courses, and was reading some of the textbooks. Now, once you think this knowledge, you'll learn enough to be a breakthrough in the field of science data.
wrong. This is just the beginning. If you think you have learned a lot, I think about how much you will learn three years later.
If you end up becoming a data scientist, you learn ten times more than they are now. This is an area constantly changing, constantly need new technologies. If you find a job once you stop learning, then you will trace the development of scientific data from beginners to become poor data scientist.
If you want outstanding performance in science data (if you're reading this, then you really want to), you need to face the fact that your learning curve will become steeper as time goes on more and more . If you do not like a lot of things to learn, do not dream of becoming a data scientist.
Just to be data geek is not enough.
You do not have expertise in other areas
So you know a little of Computer Science, and your math ability is not so bad. You do get a job in the field of scientific data?
No, you will not. You are in the IT and math skills are essential, but not enough to make you stand out from all the other data science enthusiasts.
Data scientists work in a variety of companies and industries. To provide key insights into your customers, you need to understand their fields.
For example, Kate Marie Lewis won the science data jobs within six months. But the difference is that, as a neurologist, she has knowledge of the healthcare sector.
Which areas you are good at? Do you have experience in what areas?
Try to position yourself as an expert in your field, rather than the general data scientist. This is the way you really find a job.
Your lack of business skills
So you are more analytical. Do you like numbers and quantitative analysis, you hate soft skills and interpersonal.
It does not make you a good data scientist, my friend. Soft skills are also important even in the quantitative work. Soft skills will eventually make you stand out in the interview.
In all the soft skills you can get in, you need to improve your business skills. Remember, your customers are business leaders. Therefore, they need people who understand the business. Only then can you generate valuable customer insight.
You have no meaningful contact
You want to find a job in this area, but you do not know the other data scientist? It is the time to act, my friend.
To the party. Join relevant groups on LinkedIn. Understand people attended the hacker marathon. Focus on the right people on Twitter. Please meet with other contributors GitHub projects. Do some exciting things!
Like looking for a job, like 90% of your success does not depend on how strong your skills. It depends on who can provide a reference for you, who can introduce you to.
Contact If you are LinkedIn (LinkedIn) on only your mom and colleagues, but the job has no future, it's time to do some promotion for your personal information to volunteer. If you followers on Twitter only a handful, then tweeted it. If your blog readers not to try and cross-platform search engine marketing.
Connection will come. But you have to act.
To meet, to cooperate, build your network.
You do not like the dirty work
You've heard all the discussion about machine learning and artificial intelligence. Do you think the scientific data may open the door to cooperation with the cutting-edge technology.
Maybe you will. But I assure you, you do this time will not exceed 5%.
Once you have found the ideal job, you will spend a lot of time to clean up the data. Congratulations, you have just found a new job as a janitor!
If you do not like it go home - you should not be reading this article. If after reading this article, you still want to be a data scientist, now is the time to fall in love with this dirty work.
Data Science is not a career choice. This is a profession
Data scientists are very popular individual, which makes a lot of people dabble in it. But to find a position in this field, covered is not enough. You need to work hard.
If after reading this article, you still believe that they will become a data scientist, then congratulations. You may work hard on a good road.
If at this point you're not sure whether you want to be a data scientist, to find out the biggest reason you suspect. Then start to deal with these issues. You can do it!
Original Address: https://imba.deephub.ai/p/74d6a4b068d811ea90cd05de3860c663
