The People & Systems Behind Data Science
Artificial Intelligence is on the rise, as well as the market for people and science composing the technology. To be clear, Data science is the use of math, data, AI, and The Scientific Method. Data science allows data scientists to solve complex problems. Data scientists do a lot and have the reach to change the world- and employers have taken notice. Jobs listings for “data scientists” grew 15,000% between 2011 and 2012; and today, anyone can be a data scientist – you just need a little specialized training.
In a nutshell, data scientists do three things: build artificial intelligence software, create new technology, and change the world. The extrapolations data scientists find provide actionable business intelligence to many different industries, which means that data scientists have the potential to have a greater impact on the economy of the future than many CEOs.
AI software is built easily, all it takes is a data scientist’s combination of creativity and reality. The new technology data scientists create include autonomous vehicles, space exploration, & personalized medication and education tools. This can be to revolutionize the world on a scale beyond social opinion. Data science technology often caters to energy optimization, wildlife migration monitoring, and radical efficiency.
Although artificial intelligence and data science are trends of today, the journey of data science is a 3-century-long story. It all goes back to the 1740s with Bayes’ Theorem, stating that any initial belief, combined with new data, will provide an improved belief. Bayes’ Theorem went on to become the basis for very probability calculations powering today’s AI. Data was completely revolutionized in 1954 when Leonard Jimmie Savage explained the scientific objectivity of data analysis. This went on to become the foundations of statistics, and results began proving more objective with more data.
Today, data science has fully infiltrated the common vernacular. In fact, the bulk of all data in existence today (90%) was created within the last 2 years – reported by IBM in 2013. By 2025, we will be moving at a pace creating 175 billion terabytes of data every day. Going forward, more data will continue to be generated every two years than in all the years prior for quite some time.
To prepare, as well as to understand the world’s surging data, advanced tools are needed. More directly, data scientists are more hireable than ever. Throughout 2020, there will be over 2.7 million data scientist job openings. Data scientists with skills in Python, R, PyTorch, Hadoop, and Spark hold higher chances of finding success. Specifically, data engineers, software engineers, and AI Hardware Specialists are in high demand. In common, all data scientists will need a background in mathematics and computer science – knowing Java, SQL, Scikit-learn, SaaS, AForge.NET, or machine learning techniques puts you ahead of the race.
Data science is the future, and it’s a very cool and in-demand career with great job security and stability, as well as room to grow. To read more on the job economy for data scientists, scroll down.