How Hard is it to Become a Data Scientist?
Do you want to become a data scientist? That’s a great move. Data science is a hot career that attracts many who wish to work in this competitive field. But how hard (or easy) is it to become a data scientist? Let us go over a couple of things just to build some momentum.
For starters, did you know how much data scientists make in a year? Secondly, do you even know what data scientists do and the qualifications you need to become a certified data scientist? And where can you work as a data scientist?
Well, according to the Bureau of Labor Statistics, data scientists and other employees in mathematical science occupations make about $50 bucks per hour, which translates to about $103,930 median pay per year. Not bad if you think about it.
That means you can make it big in data science, and build a career you will love for the rest of your life. Or not; if you won’t make the cut. So, how hard is it to become a data scientist? And, what do you need to make it in data science? Read on to learn more.
What is Data Science?
First things first, what is this animal we are calling data science? And what will you do on a daily basis if you become a data scientist? Do you need a degree in rocket science to become a data scientist? Or will an online data science certificate suffice? Let’s learn more.
According to the Oracle Corporation (the guys that developed Java, the programming language):
“Data science combines multiple fields, including statistics, scientific methods, artificial intelligence (AI), and data analysis, to extract value from data. Those who practice data science are called data scientists, and they combine a range of skills to analyze data collected from the web, smartphones, customers, sensors, and other sources to derive actionable insights.”
What a mouthful.
In layman’s language, data science involves using tools to analyze data and uncover what the data means. For instance, if I was a data scientist at an eCommerce company, I would analyze data from the CRM tool at my disposal to better understand what the customer needs.
But don’t get me wrong, data science encompasses many fields. What I mean is: data science isn’t all about analyzing data to make sense of the stats and whatnot. Data science goes way beyond that. If you’re new, there are many specializations of data science, such as:
Data Mining –
Just like the term suggests, data mining involves collecting raw data and turning it into meaningful information. Without mining, you have no data with which to work.
Data Architecture –
Mining data is not enough. You must develop the architecture (including physical assets, policies, rules, standards, and models) “…that govern the collection, storage, arrangement, integration, and use of data…” in your business.
Data Engineering and Data Warehousing –
Data engineering involves preparing data for analytical or operational use. Data engineers generally ensure data is flowing within an organization. Data warehousing is all about storing data in a secure, reliable, and easy-to-manage manner.
Data Visualization –
Raw data (numbers, stats, demographics, etc.) don’t make sense to the board of directors and other stakeholders. Data visualization is the graphical representation of data. It involves using charts, graphs, maps, etc. to make sense of raw data.
Artificial Intelligence (AI) and Machine Learning –
According to Britannica.com, AI is the ability of a computer to perform tasks associated with intelligent beings like animals and humans. And according to IBM, machine learning is a branch of artificial intelligence, which focuses on the use of computer programming to imitate the way human beings learn.
Data Analytics –
Data analytics is the science of analyzing data to make conclusions about that data, according to Investopedia.
Business Intelligence and Strategy –
Business intelligence involves using technology-driven processes to analyze data to derive information that organizations can use to make informed decisions.
As you can see, there are many fields in data science. You can venture into any of the above fields depending on your skills and personal preference. But which skills do you need to get started in data science? Read on to learn more.
What Skills Can Get Me Started in Data Science?
If you’re interested in data science, you’re wondering which skills you need to make it big in this exciting field. Do you need specific skills? How do you earn the needed skills to become a data scientist?
Firstly, you need a solid foundation of programming languages such as Python. Python comes with inbuilt data analytics packages that make it an excellent tool for processing complex data sets. A good grasp of Python and similar languages will help you greatly as a data scientist.
Secondly, you need excellent analytical, math, and statistical skills to thrive as a data scientist. Thirdly, you must have problem-solving and critical thinking skills that will help you to make sense of the data you’ll mine.
On top of that, you must have a curious, inquiring mind and structured thinking that allows you to identify trends from raw data. To boot, you must possess excellent communication skills to share your findings with executives and other stakeholders without any hiccups.
But, Do I Need a Degree?
A degree in data science can give you a huge advantage but you can get started without a degree. An alternative qualification that’s faster and cheaper to acquire is a certificate in data science.
A data science certificate offers you the fundamental skills you need to excel as a data scientist. You will learn everything from programming skills to manipulating data and working with data visualization tools, among other things.
The best part is you can earn your data science certificate online. An online data science certificate usually takes an average of three months to complete. That’s not fixed, however; you can expect to spend anywhere between 5 and 12 weeks to complete the coursework.
Can I Get into Data Science Without a Formal Qualification?
Say you don’t have a data science certificate or degree. Can you still get into data science? Yes, it’s very much possible! Many who started in data science are self-taught. You may not need any formal qualifications to start in data science, depending on the employer.
But how? You ask.
If you’re already working in a related field, like computer science, information technology, or business analytics, you could shift into a data science role. You just need to earn the skills you need as a data scientist.
Other than that, you could build a body of work that proves your competence in the field. If you go this route, pick a specialization to become proficient in. We’ve already covered a couple of specializations above, so you ought to be sorted in this regard.
If that doesn’t work for you, you could apply for internships or junior data science jobs. Some companies are willing to employ newbies and provide training. Brushing up on your interviewing skills can help you stand out against candidates and improve your chances of getting a job.
Where Can I Work as a Data Scientist?
Data scientists are employed in all industries, so the possibilities are endless. Some industries may require more specialized knowledge, e.g., engineering, science, or medical/healthcare. Plus, there are many roles to fill in data science, so don’t hold back.