When considering a new career or thinking about the people who populate a certain career, it’s natural to ask a few questions: what are the qualifications? What’s involved? Along the same lines, when it comes to the field of data science, you might ask—are data scientists smart?
Data scientists are smart. Becoming a data scientist requires advanced education and a solid math background. Though data scientists’ intelligence level varies, it is logical to assume that those who choose to become data scientists are typically smart individuals.
The rest of this article will detail what data scientists do, what education they must receive, their positions within the field of data science, and why it takes intelligence to perform this job.
Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!
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Determining Whether Data Scientists Are Smart
Dealing with data is not easy. Knowing how to find which data to pull, pull that data, and then analyze it clearly takes some brains. That’s what a data scientist does each day. According to Northeastern University, data scientists “…find, clean, and organize data for companies.”
This takes skills. They not only have to know how to find data, but they have to find patterns within that data to bring back to organizational leadership.
As we mentioned above, intelligence isn’t often easily measured simply by the position one holds. Knowing what is required for a particular position can help us draw logical conclusions about how much intelligence might be needed to perform a certain job or task within a chosen career field.
For example, a beginner-level job in the data science field might take less intelligence in certain applicable areas than a management-level job or senior position in the field. As you progress in the data science field into more complex positions, as with many careers, the skills you need and the intelligence you need within those skills may also logically increase out of necessity.
Let’s take a look at some of the factors that lead to the analysis that data scientists are indeed smart.
To be a data scientist, you need more than a high school diploma. At a minimum, you need a bachelor’s degree. This typically takes at least 4-5 years to earn. However, many data scientists, more than 80 percent, in fact, go on to obtain master’s degrees and even doctorate degrees. Because positions within the data science field vary, so do the degrees required to obtain them.
In general, obtaining a master’s degree might take another two years to complete, while a Ph.D. degree may require an additional three to five years of education. Before you decide to obtain a specific degree in the data science field, it’s best to know which positions require which degrees to ensure you’re maximizing both your time and financial obligation.
That said, contemplating whether everyone who obtains an advanced degree is smart is another story. In short, a data scientist who obtains a bachelor’s degree, a master’s degree, or a doctorate typically is thought of as a smart individual.
Data relates to math, so being a data scientist requires some math skills. Which skills are required depends largely on the position. A data scientist who is thought to be especially smart might be skilled in several mathematical areas, including:
- Computer programming
- Linear algebra and calculus
- Software engineering
- Machine learning
In short, it’s a logical assumption that the more you excel in these skills, and the higher the education you receive, the more lucrative, complicated position you might qualify for depending on your chosen industry.
For example, if you know one of the skills above, like statistics, you might be better qualified for a junior position rather than a senior-level position. If you know most or all of the skills above, you’re likely qualified to move directly into a data scientist position requiring complex skills and knowledge.
If complication equals intelligence, then it would be a safe bet to say that data scientists with the most advanced degrees in the most advanced positions might be the most intelligent—or at least the savviest!
There’s another factor that often indicates the position one might hold or aspire to in the data science field. It’s not even related to mathematics, either.
Are you ready for it?
It’s communication. Data scientists solve problems. They have to know what questions to ask. They have to take those questions and find data that they then interpret. The job of a data scientist isn’t done after that, though. They have to communicate their findings to the organizational leaders.
Data is arguably nothing without interpretation, so another means of intelligence in the data science field is undoubtedly your ability to take in data and then interpret and convey that data to others. It takes intelligence to think critically—that is, to take in information, process it, and then communicate it to others. It’s not a skill that should be taken lightly; it takes time to master.
Can Data Science Be Learned on the Job?
As with most jobs, a lot of the learning is done while working in the job itself. Like any company, you might become a data scientist at a company and then move into different roles or sectors within the company as you progress up the work ladder. Here are some positions you might hold as a data scientist:
- Data analyst: This might also be called a business analyst, financial analyst, or market research analyst. They deal mainly with data mining and analysis.
- Junior data scientist: This is slightly more technical than a data analyst. The junior data scientist takes on less complex tasks than the data scientist but more complex tasks than the data analyst.
- Data scientist: This is a much more technical position than that of a data analyst. Data scientists write algorithms, and they often build statistical models. In short, they take complex data and make it useful.
Showing your intelligence and ability to adapt within the organization and learn new skills might speed up that process and prepare you for more lucrative jobs requiring more intelligence within the data science field.
Where Do Data Scientists Work?
Data scientists work in both large and small companies. After all, more companies are increasingly looking to leverage data to improve, maintain, or grow workflow. That being said, you might find the majority of data scientists in these companies in particular:
- Tech companies
- Financial organizations
- Higher education
- Company “giants” such as Facebook, Google, Amazon, and Netflix
How to Become a Data Scientist?
If you’re considering a career as a data scientist, one of the great ways to learn about the profession is to read about it; learn what’s required. Learn some of the skills data scientists employ every day. Then, determine if it’s a career that might interest you.
This can help if you’re considering spending a large amount of money on a degree to become a data analyst, junior data scientist, or data scientist. If you’re looking for a resource, the book Data Science for Beginners provides an excellent introduction to the field of data science. Please give it a read. At the very least, you’ll feel a bit smarter yourself after examining some of the skills data scientists use on the job every day.
Author’s Recommendations: Top Data Science Resources To Consider
Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.
- DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
- IBM Data Science Professional Certificate: If you are looking for a data science credential that has strong industry recognition but does not involve too heavy of an effort: Click Here To Enroll Into The IBM Data Science Professional Certificate Program Today! (To learn more: Check out my full review of this certificate program here)
- MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
- Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.
Logically, yes, data scientists are smart. They undergo many years of education and have to be skilled in complex mathematical skills. Intelligence takes many forms, and there is not a single intelligence level that can be attributed to all data scientists.
As we’ve seen, factors such as education, skill set, and job duties often determine what a data scientist does. The required education, background knowledge, and skillsets vary widely, making it difficult to state what specific intelligence is required. In short, it takes intelligence to understand and interpret data, so a data science career typically means one is smart.
BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.
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