15 rules to a career in data science

15 Rules to Becoming a Data Scientist

Bootstrap your journey into data science in 4 months.

Who are Data Scientists?

They are big data wranglers. Data scientists take an enormous mass of unstructured data and use their formidable skills to clean and organize it. Then they apply all their industry knowledge and contextual understanding to uncover the hidden solutions to business challenges.

Organizations are increasingly relying on the expertise of data scientists to sustain, grow, and outdo their competition. Consequently, as the demand for data scientists increases, the discipline presents an enticing career path for students and existing professionals.

So, here are the 15 rules you need to follow to become a pro at data science.

 

Rule #1: Embrace Chaos

The path to becoming a data scientist isn’t a linear one. It’s not textbook learning; it’s more of a practical one. Chaos is the part of the learning process, it’s the necessary pre-condition. There might be situations where you want to step down from this path or re-think pursuing this path-breaking career. It’s just a phase that comes in the life of every person who is taking up data science as a career. So, you need to focus on the learning process as against the broader debating over the decision. Enjoy this beautiful journey by pushing yourself a bit more to accomplish your dream career.

Rule #2: Learning is organic  

Starting the journey into data science is not easy. You need to be ready to learn a lot. That being said, learning is more organic than synthetic. You need to understand that acquiring all the skills will take its own course of time. It’s like learning to drive a car – it’s a step-by-step process. You only learn it with constant practice and self-motivated attitude. You need to keep a similar inclination when you are embarking on your journey as a data scientist.

We help learners thrive. It reflects something beyond succeeding, something more healthy. You are like a plant that thrives in various conditions for growth, while we ensure it by creating those conditions that are right for you.

 

Rule #3: Data Science is in FLUX

The uptick of interest in data science and machine learning platforms is driving an increasingly crowded market.The rapid changes in the market are a signal to the industry at large, including you, to keep a close eye on things. There are certain disciplines like ‘thermodynamics’ that have been a slow evolution, but data science is one such discipline where every second there is a new development that changes the entire dynamics of this industry. Moreover, data science is not just limiting itself in IT, it is also bringing an all-new innovation in other sectors like banking & finance, retail, food, education, telecom, stock markets, etc. as well. Necessity is the mother of all inventions.

 

Rule #4: Stop searching for ‘Right’

It’s ok to think everything should either be right or wrong. So, you tend to go with logic, an algorithm, or a binary process. But that’s not the case when you choose the field of machine learning. It’s way beyond your thought process. Actually, you need to switch the mindset.

Let’s take an example.

You built a program with 60 percent accuracy and minimum financial resources, while another person made it with 59 percent accuracy at the same investment; and then there is a third person who built it with 70 percent accuracy, but he invested a lot of money building it. The market is already hungry for new inventions, but everyone wants it at a bare minimum cost. So, stop thinking of only delivering the right. In this example, probably you could win the bid over others.

 

Rule #5: Don’t mistake vagueness for vastness

Becoming a data scientist requires expert skills in various fields like software development, database query languages, machine learning, programming, mathematics, statistics, data visualization, etc. This seems like a lot – and many do get discouraged once they go through this immense list of skills that they are told is necessary to become a data scientist. This, however, is not the case.

As many senior data scientists, who also teach at GreyAtom, say – one need not possess a lifetime worth of data scientist skills to start learning data science because “Data Scientist” is like a blanket job title where each one is of a different specialization.

Yes, it is vague, but not vast.

 

Rule  #6: Math is the only language

By the rule of the thumb, you need to know the elementary mathematics like the back of your hand. To make an obvious statement: mathematics underpins all areas of data science. This subject may seem intimidating, but it is the only language that will make you do wonders. So, you need to be comfortable with this subject.

 

Rule #7: Be hands-on, practice daily

Intellectual curiosity is an important pre-disposition for a data scientist. You cultivate and sharpen it by “always wanting to know a bit more about data” when analyzing it. The best way to hone your skills as a data scientist is to get industry exposure. Start an internship or join a boot camp or if you already have experience as an Analyst, get started with a job.

This only comes through a lot of practice. Participating in competitions is a good way to push yourself to learn something new, to collaborate on different projects and to deal with data other than those we are used to analyzing in our day jobs.

 

Rule #8:  Focus on Impact, generate momentum

Data scientists hold the key to unveiling better solutions to old problems. While you are on the journey of becoming a data scientist, you need to focus on creating an impact. This can only be achieved through constant learning. Explore unknown transformative patterns in data science and machine learning. This will usher in innovation. While boosting your confidence, you are only making yourself better every day.

 

Rule #9: Look beyond competition

The best way to compete is looking beyond the competition. While you are learning, you are not here to compete with others but to better yourself. The best way you can do this is by taking the path of sustained learning, constant experimentation, and taking up new challenges in the field of data science and machine learning.

 

Rule #10: Hang out with other Data Scientists

One of the proven ways to becoming a pro at data science is to learn from data scientists themselves. They are the ones who have been the inventors and the innovators in their respective industries. You can network with them at meetups or connect with them through professional social media platforms.

 

Rule #11: Don’t burden your future self

By using the term “Future Self,” we want to get you thinking about how your actions at the moment might affect you either positively or negatively later in your life. As a data scientist, you want to see yourself going up the career ladder in the future, so don’t make decisions that could go against you in the future. We’re here to guide you to reach your goal with ease.

 

Rule #12: No one knows it ALL

As a data scientist you may feel that asking help from people with things that you are unfamiliar with, means that you are not smart enough. So, therefore, you start it without any proper guidance or knowledge and try to figure it all out by yourself. But the truth is, no one knows it all; neither would anyone ever succeed in knowing it all.

 

Rule #13: Pain is part of the Growth Process.

No pain, no gain. That’s the philosophy you need to follow when you choose to become a data scientist. There will be situations where you want to step down and rethink your decision. But that wasn’t the reason why you took up this path. Don’t let your dream die out because this struggle will be a part of your growth process. So, keep moving until you achieve your dream.

 

Rule#14: Inflection Point is “Point of Sustainable Practice”

Sustainability encompasses maintenance. A sustainable learning plan is a necessary component to the long-term success of being a data scientist. Putting this into practice proactively will only help you become a better data scientist. There will be a time when you won’t have to force it anymore, but it will come naturally to you.

Always remember, becoming a data scientist is like learning to drive a car.

 

Rule #15: Data Science is a team sport, don’t learn it alone!

The greatest challenge of the big data revolution is making sense of all the information generated by today’s vast digital economy. As a data scientist, you are not working in isolation. You need to need to team up with data engineers, developers and business analysts, and learn how the team can outthink today’s challenges and problems to create new opportunities and possibilities for tomorrow.


Conclusion

Spend a week conditioning yourself for each rule and in 4 months you will be all set to kick start your journey into data science.

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