Being a data scientist is one of the best professions a person can be in right now besides, of course, being the president of the United States.

“Enterprises have suddenly realized how important data is and the need to make sense of all the unprocessed information, thereby shooting up the need for a professional data scientist” – according to Karl Hoods.

As time wears on, businesses will need to make critical decisions and handle complex problems that they might face due to high competition, fast track technological innovations and a rapid increase in awareness among customers. This is where many companies find data to use as a tool to help them thrive in the market. There is a large amount of data being accumulated daily, and to make any sense of them, companies need staff with knowledge and skills in statistics, coding, data preparation, visualization, and machine learning.

Data scientists are very rare to find because of the number of skills that are needed to become one. This brings us to the next section:

Who Is A Data Scientist?

A data scientist is a relatively new role in business ecosystem. A data scientist is an expert skilled in giving solutions to difficult problems, especially those involving available data. A data scientist is also trained to be curious about hidden problems and exposing them before exploration.

A data scientist can be a good mathematician that has a broad knowledge of computer science while also being able to spot current trends.

Ten years ago, data scientists were not popular. Suddenly, businesses started to understand the effect of big data on critical decisions and revenue, and then the rush for a specialist who can make proper sense and turn this raw information into business insight began.

Why Are There So Many Smaller Roles Right Under The Data Scientist Umbrella?

As companies begin to find a use for data scientists, they also develop needs for more skill sets. There is a need to marry the technical aspect of data with the company’s business, communication and its clients. All these roles are being crammed into the small box called data scientists. Businesses want data translators, data leaders, etc.

According to research done by SAS UK, it was learned that more than 50% of data scientists suffered stress due to their huge workload.

By implication, data scientists have had to overwork themselves trying to cover grounds to meet up with the enterprise demands. The role had to be split into smaller sub-roles for proper maneuvering.

What Does The Future Hold For Data Scientists?

Since the job description of data scientists used to be too stretched, businesses are now shifting to sector-specific data scientists and moving farther away from the general data organizers. It implies that businesses are more in need of data analysts with a much more specific and specialized skill set and not one with domain knowledge of the subject.

A data scientist can have skills of encompassing and analyzing data without being a domain expert.

As it stands, there are newer technologies in the IT sector that require specialized skills – one that a domain data scientist might not possess, and it seems several years from now, these experts are going to have to fall back into the job-hunt market.

What Can Data Scientists Do To Remain Relevant?

For a data scientist to remain relevant in the future, he needs to be more area-specialized – taking the trends into cognizance. However, some experts do not believe a data scientist is standing on quicksand.

The Chairman of IT and Digital Leadership for Berwick Partners, Matt Cockbill, don’t believe that data scientists may become redundant in the nearest future. According to him, more career paths are bound to evolve from data scientists soon, but the importance of data engineering and data science skills isn’t set to fade just yet. Instead, it has a way of causing reforms to the surrounding environment, delivering an unending chain of demand.

It means data scientists may still have a bright future of taking on business challenges and giving them priceless pieces of advice that will push the company to excellence.

Since the role of a data scientist is one that is hard to fill, someone with a data scientist certification would be a hot commodity in the job market.

How to Obtain a Data Science Certification

Those who want to obtain a data science certification are either undergraduates or folks who want to shift careers.

As a student, a data science certification is obtainable from an institution that offers the degree. Many institutions offer classes in data science and analysis.

Professionals looking to switch career lanes and jump into data science can obtain the certification too. Most data scientists have basic knowledge in technical areas like statistics or data analysis. Even if you’re from a career background in economics or business, you can obtain a data science certification.

But how is that possible? I mean, how can someone with a non-technical background end up in the same career field as one with basic tech knowledge?

The trick is in understanding the inherent abilities that these individuals have in common with data scientists. Do you have a longing always to provide a solution to problems? Are you curious and want to understand the mechanism responsible for keeping the work environment in motion? Do you have the ability to communicate ideas or information clearly that even a layman can grasp your message? If these questions can be answered as yes, you have everything it takes to acquire a data science certification.

All that is left is further specialized training with special tools to make you a data scientist.

These specialized tools include gaining knowledge in areas like

  • Machine Learning
  • Statistics
  • Coding
  • Reporting technologies
  • Data visualization
  • Databases like Postgres and MySQL
  • MapReduce and
  • Hadoop

These are areas that can be learned from the comfort of your home. If that wouldn’t be much of a motivation for you, you can take part in a Bootcamp or enroll for online courses. With those in place, networking is the next thing to do. Get into a data scientist community, and there you’d learn more about your job roles, and in case you want options, you’d discover where you can find the best offers.