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The concept of a data scientist is so new there’s a debate over whether it’s a real term or just media hype. Even the requirements for becoming a data scientist are in flux because data science itself is being defined in real-time. We want to add some clarity for anyone looking to pursue a data science career by identifying what you need to do to become a data scientist.
How to become a data scientist
You don’t need a PhD to become a data scientist. Unlike a rocket scientist or a doctor, there are no prerequisites or tests to pass to become a professional data scientist.
The term itself came into existence when big data made previous job titles inadequate. What do you call someone who uses software engineering, coding, statistical analysis, and data visualization to extract answers from data and also builds models to find new questions and potential solutions? If you think that sounds like a scientist, you’re right! “A scientist is someone who systematically gathers and uses research and evidence, making a hypothesis and testing it, to gain and share understanding and knowledge,” according to the Science Council.
By using that definition and applying it to big data, we see how the term data scientist came into existence.
Credit: Stephan Kolassa
If you were thinking about becoming a data scientist, there are several potential routes.
The traditional path is through academia in the pursuit of a degree in Computer Science, Statistics, or another related field. An entry-level data science job found on Glassdoor may require a bachelor’s degree while a senior role may need a Master’s or PhD. This could be a good route to explore for a recent high school grad who will enter a highly competitive field in a few years and wants to stand out. But the traditional is not the only route to take.
Consider everyone with experience as a software engineer or with skills necessary to become a data scientist. Going back to college for an advanced degree might not be feasible. In fact, it might not even be necessary. There are no absolutes here because all jobs are different and companies might be looking to fill a role where an advanced degree is required.
It’s about having the right background for the job you want. For experienced coders, demonstrating mastery of data science skills, including languages and examples of models you built, makes you qualified for a data scientist position.Bootcamps and tailored programs have emerged to fill the gap between higher education and the shortage of data scientists.
A good data science bootcamp eliminates the educational barriers while providing the necessary training and tools to enter the field as a qualified candidate. A rigorous curriculum will cover all the necessary data scientist skills and languages. Students will have live projects and an online portfolio by the end of the bootcamp.
Data scientist skills
If you’re endlessly curious, love to code, are a problem solver, and are not afraid of technical challenges, then you have a data scientist mindset.
A data scientist is a storyteller that’s always probing deeper to find new insights — and they do that through multiple languages.
Data scientists are well-versed in statistical computer languages, such as R and Python, along with data management systems like SQL. Coding is vital for a data scientist, but it’s not the only thing they’ll be doing as part of their jobs. Data scientists work as part of a team to solve problems for a company. They typically work with data analysts, who are translating business needs to the scientist. And the scientist has to understand the task at hand while being able to convey how that may be achieved.
Let’s use Amazon and Netflix as an example of data scientists solving problems. Both companies want to sell their services as the most convenient and best option for any consumer. Amazon and Netflix need intuitive ways to highlight products that would appeal to a customer. Data scientists can solve that problem by creating algorithms and models to steer customers in the right direction. We see this in action through recommendation systems developed by engineers, analysts, and data scientists.
While it’s already considered the hottest job in America, we expect even greater demand for data scientists for years to come. Companies are collecting a lot of data and need data scientists to unlock the stories within that information.
Data scientist jobs
Data scientist jobs have grown 650% since 2012, according to LinkedIn. That upward trend will likely continue for at least the next decade. The U.S. Department of Labor doesn’t have a specific data scientist profile, but we can look for trends in related areas: Computer and Information Research Scientist jobs, for example, are projected to grow by 19% from 2016 to 2026, according to the U.S. DOL’s Bureau of Statistics —much higher than the average for all other jobs. IBM, too, predicts data scientist jobs to grow 28% by 2020.
The financial services and tech industries employ the majority of data scientists and data analysts, according to a survey conducted by Burtch Works, a data science and analytics recruitment agency. While 54% of data science jobs are currently within these two industries, more industries are seeking data scientists and analysts. Opportunities can also be found in healthcare, retail, and insurance.
If an industry can use big data for insight, you can expect to see jobs for data analysts and data scientists. That’s why data scientists are here to stay and not a media creation.
You will need to speak the language of a data scientist by learning SQL, Python, and R, and have some good math skills.
Both computer science programs and bootcamps allow people to learn these skills.
Our free Online Data Science Bootcamp Prep covers the basics of data science.
Head of Data Science Education
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