Data Science Job Growth in 2021 and Beyond
The year 2020 has been tumultuous for many industries, yet data science experienced significant demand and growth. According to a recent Dice Report, the demand for data scientists in 2020 has increased by an average of 50% across healthcare, telecommunications, media/entertainment, and the banking, financial Services, and insurance (BFSI) sectors, among others.
For many businesses, Covid-19 caused significant disruptions and profit losses this year, yet gave way for many opportunities in the tech sector. Data scientists helped businesses dramatically improve the effectiveness and efficiency of processes and operations to meet shifting online workforce needs with the help of big data, cloud computing, machine learning, and more advanced Artificial Intelligence (AI) applications. Increased demand has allowed data scientists the opportunity to drive huge advances in client data management, Robotic Process Automation (RPA), cyber security, finance, healthcare, manufacturing, logistical supply chain AI, retail, workplace communication, and e-commerce. These fields will undoubtedly continue to need data science talent in 2021 and beyond, as data scientists help companies increase their capacity for big data and make sense of newly digitized business models and digital revenue opportunities.
Whether you are curious about a career in data science or want to know what specialization to lean toward, we are here to help break down the numbers for you. Let’s take a closer look at the data science job market and projections for data scientists in 2021 and beyond.
What is the career outlook for data scientists?
A career in data science takes considerable dedication, a passion for data, and a special kind of curiosity about problem solving. Although it is a challenging path, there are many reasons why you should consider a career in data science. Consider the following data science job growth statistics:
- Data scientists work within most major industries where growth is happening. The finance industry was one of the first to take notice of data scientists and understand what data scientists do. They not only found value in the ability of data scientists to analyze data to make predictions, inform decision making, and prevent losses, but identified the long-term profitability of leveraging their unique skill sets. Today, the majority of data scientists work within the tech sector, although those numbers are changing. A report by Deloitte Access Economics concludes that 76% of businesses plan to increase spending over the next two years on data analytic capabilities, opening the doors for increasing needs within all fields requiring analysis and feedback, including energy, the internet, manufacturing, financial services, healthcare, cyber security, telecommunications, retail, construction, transportation, education, government and non-profit organizations. This is great news for small businesses and Fortune 500 companies alike, who will benefit from leveraging data analysis to strengthen their business strategies and increase profits.
Not only did IBM predict the demand for data scientists would surge by 28% in 2020, but the Bureau of Labor Statistics considers data science in the top 20 fastest growing occupations and has projected 31% growth over the next 10 years. Additionally, Garner projects worldwide IT spending will increase from $3.9 trillion in 2020 to $4 trillion in 2021. Data from the recruiting firm Robert Half shows that 69% of IT managers in the first half of 2020 intended to grow their teams in areas like cybersecurity, cloud computing, business intelligence, database management, and DevOps, but 86% had a challenging time finding talented professionals. This indicates a discrepancy in the needs met and potential opportunities waiting in 2021.
- Big data needs will continue to grow. Big data describes the large collection of data that grows exponentially over time in size and complexity that traditional data management tools are unable to efficiently store or process. Big data can be structured or unstructured, and is used by companies like Amazon and Facebook to grow automation, advertising algorithms, and meet growing data capacity needs. As a recent Forbes Article suggested, companies like Netflix that lean on big data analysis to inform decision making will make better decisions and take more informed risks, in turn reaping greater rewards and revenue. This means similar analysis and decision model strategies will only be more valuable to companies in the years to come. According to a recent Markets and Markets Report, the global market for big data is predicted to grow from $138.9 billion this year to $229.4 billion by 2025, with the data science platform growing 30% by 2024. This means that not only will big data be more accessible globally, but it will have steady upward growth as data scientists increasingly work to streamline data management and normalize the mainstream use of machine learning algorithms and big data analytics.
- Greater cloud infrastructure is coming. Cloud computing is the delivery of databases, servers, storage, software, networking, analytics, and intelligence completely online, allowing individuals and businesses to save files to cloud databases and retrieve them at will. Major cloud providers like Google Cloud Platform, Amazon Web Services, and Microsoft Azure have growing cloud-based needs for machine learning, data storage, and analytics and have even embedded and expanded their AI offerings for public and hybrid cloud deployments this year. According to a recent O’Reilly Report, 88% of organizations used some form of cloud infrastructure, with most surveyed organizations planning to grow their cloud capacity within the year.
Due to the unforeseen virtual needs for most companies in 2020 due in large part to Covid-19, cloud needs likely surpassed most projections for the year. In addition, as more data and analytics moves to the cloud in 2021, business leaders will likely work more closely than ever with data teams to utilize cloud systems efficiently to prioritize workloads, optimize costs, and accelerate innovation. A report from Forrester Research predicts cloud infrastructure will grow by 35% to $120 billion in 2021, with 25% of developers moving to serverless and 30% moving to use containers regularly by the end of 2021. This means greater demand for multi-cloud container development platforms and greater opportunity for innovation within large and small tech environments alike.
- The exponential potential and growth of Machine Learning and AI will keep data scientists busy innovating. AI refers to the simulated human intelligence programmed into machines, while Machine Learning refers to the application of AI that allows systems to learn and improve from experience without being explicitly programmed. According to a recent Forbes Article, 28% of US homes will be “smart” by 2021 thanks to Machine Learning and AI that will interact with real-time data and automatic processes. AI from chips to software will continue to bring insight, efficiency, and cost savings to the digital landscape next year. Notably, AI and Robotic Process Automation (RPA) has enabled companies to work more efficiently and use employees for more creative, complex tasks. Still, by some estimates only 15% of companies currently utilize 50 or more bots. This leaves tremendous growth potential for AI and Machine Learning. According to LinkedIn’s 2020 Emerging Jobs Report, data scientists showed 37% annual growth this year. In fact, data science has topped the report for three years running, citing AI as a significant contributing factor. This means there has never been a better time for a career change to the tech field, with innovation propelling job security and growth.
With so much potential, it is no wonder data science was named “sexiest job of the 21st century” by Harvard Business Review. Undoubtedly it will evolve with the ever changing needs of the digital landscape, but the field of data science will leverage its reputation for years to come, ushering in talented and enthusiastic data-savvy statisticians who will transform tech in ways we cannot even yet imagine.
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