How To Become a Data Scientist?

What does it Require to become a Data Scientist?

Big data is the buzz word circulating in tech circles nowadays – online and otherwise! From tech giants like Google to mainstream MNCs such as Netflix, Wal-Mart, all the major players are focusing on big data. The data scientists, as a consequence, are in huge demand. It pays to become a data scientist, though the profession is relatively new and still in a nascent stage. Data scientists are professionals who let such giants unravel useful and new information that eventually let them stay ahead in the race.

What are data scientists after all?

Data scientists deal with enormous amounts of raw data compiled from diverse sources. They also analyze and filter the vast amounts of data to reach findings and conclusions that can be relevant and useful for companies they are working for. They are assisted by data analysts in the process. They need to make use of specialized software solutions and procedures for their work.

Above all, they need to make full use of analytical skills and technical knowledge. The client companies get insight into hitherto unexplored aspects of their operations through findings of data scientists. For example, a manufacturer can get more accurate insight into customer preferences or develop products with a reduced error possibility.

Types of data they have to deal with may be varied. It can be both structured and unstructured in nature. The data can be obtained from both online and offline sources involving social media sites. Examples include MasterCard processing a myriad of applications every day and Amazon recording thousands of varied customers questions though live chat, phone, and email.

become a Data Scientist

What it takes to be a data scientist

It is a relatively new career option, as already stated, and there may be a few tailor made courses where you can enroll to become a data scientist. However, every data scientist needs to possess certain skills and develop a few more perhaps. Experts say, a data scientist needs to be well versed in three domains to make it big. These are: math/statistics, business domain, and computer programming skills. Learning on the move is something nearly all data scientists and analysts have to do eventually as well.

Skill in computer programming language is what a data scientist needs primarily. There are so many languages and you may choose a prevalent one to develop a strong foundation. Learning big data platforms like Apache Hadoop is also a prerequisite. However, the platform and setup may vary from one company to another.

Blending creative skills, experimentation with a scientific mindset is a requirement data scientist have to comply with. A data scientist learns a lot when working on many projects and he has to do many new things without prior experience too. Contextual understanding is also another factor here. Carrying out new experiments and deploying new filtering techniques may be required.

A data scientist also needs to develop an intimate understanding of the business needs of the organization he is working for. This is something not taught in any course. For this, it is necessary to keep your eyes open and study the niche the company belongs to. It may also be necessary to observe steps adopted by rival companies belonging to the same sector for data analysis.

Apt educational and technical qualifications

Most of the successful data scientists are highly qualified. The educational qualification may include degrees (either graduate or post graduate) in subjects like statistics, mathematics, and computer science. Some of them are Ph D holders too. As for skill in programming languages, you may think of doing a course in Python or Perl. Knowledge in cloud tools such as Amazon S3 will be advantageous as well. While this may not be a mandatory aspect, developing expertise in large scale database apps like SQL can be beneficial for such professionals.

Is the career suited for you?

If the lure of big bucks and working with top MNCs seems lucrative – think of the downsides of the career. There is nothing like a perfect job and the same can be said about the job of a data scientist too! It is not only about dealing with petabytes of data – you also need to compile the data in span of time, be a pro at teamwork. Good PR skills are a prerequisite. As a data scientist – you will be dealing with various departments in a company and co-ordination with plenty of people will be required. It can be stressful and multitasking will also be required. You should have people and verbal skills as already insinuated.

How rewarding the job is

The stress and downsides notwithstanding, the job of a data scientist can be pretty rewarding, at least from the monetary perspective. Even the entry level candidates earn close to or more than $100,000 per annum but in a recession you may not earn this much to start. With time and experience, the pay package is only likely to increase.

Summing it up

While having specific qualifications and developing new skills is mandatory for becoming big data scientists, patience and perseverance are two qualities that pay off in the long run, say the experts. Problem solving, data segregation, and relevancy analysis – these are skills no one can develop overnight. It may take you years of training and effort before you can secure a plum job as a big data scientist.