The importance of data has grown exponentially over the last decade, giving rise to the emergence of a new profession: the data scientist. This role has been ranked consistently as one of the highest paid, most satisfying, in-demand jobs for the last 5 years. Coming in at number 3 on Glassdoor’s 50 Best Jobs in America 2020 list, and seeing a 37% annual increase in demand according to LinkedIn’s Emerging Jobs Report 2020, it’s clear that the data scientist is here to stay as an integral part of the modern workforce.
“Data science is a field that is seeing continued growth on a tremendous scale.”
LinkedIn, U.S. Emerging Jobs Report 2020
Over recent years, data science has become fundamental to many sectors such as finance, insurance, agriculture and IT companies and there’s no sign of this trend slowing down. It looks like IBM was right when they predicted back in 2017 that, by 2020, the demand for data scientists would grow by 28%. Fast forward to summer 2020 and we’re looking at one of the hottest in-demand careers. Even in light of the economic disruption caused by the Corona pandemic, machine learning and data analytics are more important now than ever for reopening businesses around the globe.
What does a data scientist do? How can I become a data scientist? Do I need a postgraduate degree to get hired? If you’re asking yourself these questions then keep reading. This post will explore what it is that makes a data scientist so important to modern businesses, and which skills you need to make the transition into this career path.
Read on to find out how you can upskill to get a high-paying data science job. No time to read more? Check out the IBM-certified Master’s in Data Science program bundle available on ODEM.
What is Data Science?
Data science emerged as a field alongside the rise in the use of computers throughout the 20th century. It combines the long-established field of statistics with the digital frontier of computer science. It wasn’t until 2001 that the term ‘data science’ was coined by William S. Cleveland, and this increasingly popular discipline was defined.
“Data science is the process of using algorithms, methods, and systems to extract knowledge and insights from structured and unstructured data. It uses analytics and machine learning to help users make predictions, enhance optimization, and improve operations and decision making.”
The goal of data science is to understand and make effective use of large and complex data sets often referred to as big data. Patterns and trends are identified through collection, analysis and modeling. This multidisciplinary approach uses machine learning and statistics to build prediction models that can forecast behavior and influence business decisions.
What Does a Data Scientist Typically Earn?
Data science is one of the highest-paid careers. According to the latest numbers on indeed.com, the average yearly salary for a data scientist in the USA in 2020 is $122,250. Even at entry-level, the salary is still competitive. A data scientist with less than a year’s experience can take home an average of $103,386.
One reason data science is such a profitable career opportunity is that companies are realizing the immense amount of value that a data scientist can bring to their business. The competition is fierce over hiring, and the most qualified data scientists are hard to come by.
The highest-paid data scientists are typically experienced, expert-level professionals in data-driven tech companies like Google, Apple and Twitter. The industries that tend to offer the most competitive salaries include cloud services, social networking and banking & finance.
What Does a Data Scientist Do?
There is a sheer overwhelming amount of information that is created, collected and stored by companies in today’s digitally connected world. This would be impossible to digest without the help of skilled professionals armed with the right analytical tools and mindset. And hence, the data scientist was born!
Much of what a data scientist does daily is to collect and organize data into a machine-readable format to be able to extract valuable insights from it. A data scientist uses software and tools combined with statistical and mathematical models to make sense of big data.
Which Skills Are Required to Become a Data Scientist?
A data scientist might build a prediction model for an eCommerce company to help determine which products will be the most popular, or they may develop an AI to prevent fraud in the banking sector. Regardless of the diverse applications, there are core technical skills and competencies any good data scientist should possess:
- Python for Data Science
- Hadoop Platform
- Apache Spark
- R programming
- Machine learning & AI
- Data analysis, modeling and exploration
- Business analytics
- Deep learning
- Natural language processing
- Data visualization
Get in-depth training in all these skills and more on the IBM-certified Master’s in Data Science program.
Do I Need a Diploma or Postgraduate Degree to Get Hired?
The world of data science is constantly evolving so it’s important to stay up-to-date and continuously refine skills. Whether you’re a seasoned professional or an aspiring career starter from any educational background, the key ingredient to enter the world of data science is an analytical curiosity.
Due to the in-depth knowledge required to analyze big data, data scientists often have a postgraduate diploma such as a Master’s or a PhD in computer science, social sciences, physical sciences, or statistics. There are exceptions, however, plus several other related positions in a data science team or department. Roles such as data analysts, big data engineers and analytics managers require a subset or a specialization in one or more of the fields of data analytics and computer science.
Data science is not all about mastering the tools and technology, those who possess soft skills such as good communication skills, critical thinking and business know-how are more likely to succeed. In fact, the best data scientists are not only good with data, but they are also adaptable team players and excellent storytellers.
Why Are Data Scientists in Such High Demand?
“One of the biggest problems in the big data industry is the lack of people with deep analytical skills. Looking at the data growth statistics, it’s clear that there are not enough people who are trained to work with big data.”'
Just think for a second about how we lead our digital lives. Shopping, reading news, listening to music, searching for information, communicating with friends: all this activity and more is being constantly tracked and collected. Combine that with all the data produced through financial, medical, government, education and other sectors and you’ve got a pretty substantial amount of valuable information. In fact, the amount of data in our digital universe is doubling in size every two years - reaching an astounding 44 zettabytes (44 trillion gigabytes) in 2020!
“A new kind of company — we call them insights-driven businesses — has formed. They are growing at an average of more than 30% annually and are on track to earn $1.8 trillion by 2021.”
Companies who embrace data science and use it to influence all aspects of their business are much more likely to gain market share than the competition who neglects to use data to their advantage. The key to success is making fast, informed decisions. A data science team provides just that.
Which Industries are Being Disrupted by Data Science?
Some of the earliest adopters of data science include finance, eCommerce and healthcare industries. The applications for businesses are endless and we’ll continue to see more and more industries embracing data as core to their business decisions over the coming years.
“By 2021, 69% of U.S. executives say they will prefer job candidates with data skills, yet only 23% of educators believe their graduates will possess these skills.”
Business-Higher Education Forum (BHEF), Investing in America’s Data Science and Analytics Talent: The case for action
Over the next 5 to ten years analytics-driven organizations will prosper. The demand for talent will only continue to grow as the amount of data to analyze continues to expand and as sectors as diverse as libraries, professional sports, firefighters and construction discover the role advanced data analytics can play.
In short, there are many reasons to choose a career in data science. Demand for talented data scientists, analysts and engineers will steadily increase as technology evolves and as adoption continues. There are guaranteed job opportunities in diverse industries, as well as many data-focused roles and specializations to choose from. Talented individuals will go far and earn well for years to come.
You don’t necessarily have to have a Masters degree or PhD to get hired, the right mindset and professional experience in related areas can also give you a solid start. The best way to transition to this field is to get insights into the main technologies and disciplines, even if you don’t become an expert straight away. The Master’s in Data Science program on ODEM is a great way you can kick-start your career in data science. The self-paced program gives you hands-on exposure to the key technologies including R, Python, Tableau, Hadoop and Spark, plus an IBM-certified qualification on completion.