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Considering a career in data science? It’s not too late!

The field of data science celebrated its 50th anniversary in 2017. It was first recognized by the name “data analytics” in its pioneering research paper ‘The Future of Data Analysis’ in 1970 and ever since the importance of data science has been increasing exponentially. From its roots in theoretical statistics, data science has come very far and now dominates all the fields of science and engineering.

We are now in the Information Age and the 21st century has always been associated with the information explosion. It refers to the availability of huge volumes of data, data from all the walks of life, and the world we live in is literally shaped by data.

Data science as a career:

Data science is a versatile field that employs various methods, processes, and algorithms for the extraction of insights from structured or unstructured data. ‘Data scientist’ is a career that emerged a few decades ago and has become a highly sought out profession ever since.

The importance of learning data science is evident from the fact that the world’s top universities like UC Berkeley, NYU and MIT initiated their data science programs decades ago. The University of Michigan launched its $100Million “data science initiative” in 2015.

APPLICATIONS OF DATA SCIENCE

In recent decades, the implementation of data science has increased manifold and its applications, countless. We’ll briefly mention a few to showcase the range and implications, but we are have barely scratched the surface of the potential of data science.

  • Web search engines like Google uses data analytics to sort and collate huge volumes of data and provide the user with millions of results in less than a second.
  • Digital marketing has boomed using the data sciences which enable to analyze the usage trends of a person and present them with targeted advertisements.
  • Analyzing a large sample of facial feature data has been enabled almost accurate face recognition algorithms. Similar goes for speech recognition.

Data science has umpteen other applications – starting from price comparison websites like shopping.com, fraud, and risk detection in the banking sector, product planning, and promotion, gaming, logistics to airplane routing.

IMPLICATIONS

Data science not only speeds up the existing applications and use cases, but it also transforms the way we approach problems. It carves new methods to solve existing problems and its capability has opened new avenues that were previously not possible. An anywhere a large amount of historical or usage data is available, data science has an application or will find one.

Data science as a career

In recent decades, the implementation of data science has increased manifold and its applications, countless. We’ll briefly mention a few to

  • Web search engines like Google uses data analytics to sort and collate huge volumes of data and provide the user with millions of results in
    less than a second.
  • Digital marketing has boomed using the data sciences which enable to analyze the usage trends of a person and present them with
    targeted advertisements.
  • Analyzing a large sample of facial feature data has been enabled almost accurate face recognition algorithms. Similar goes with speech recognition.

Data science has umpteen other applications – starting from price comparison websites like shopping.com, fraud and risk detection in the banking sector, product planning and promotion, gaming, logistics to airplane routing.

Does it help existing jobholders?

A common and widespread misconception is that data science is a separate career of its own and that the existing jobholders cannot do much in that avenue. While the former is to a certain extent, true, the latter is far from accurate.

Data science is a boost to the existing ways of business. In time, it is set to redraw the process flows and change the entire landscape of industries. But implementing data science and finding new and innovative applications for this field requires vast domain-specific knowledge and expertise that can only come from the existing workforce of the different sectors.

TRAINING IN DATA SCIENCE IMPROVES ON-JOB PERFORMANCE

Training in data science is not only helpful in landing a high paying job. It also helps to improve the quality of one’s work in fields other than engineering too. One such case is as follows.

Data science is revolutionizing the edtech field.

Tech-savvy teachers are using their training in data sciences to improve the classroom engagement, student grades and personal growth of students. Georgia Tech researcher Jon Bidwell helped the teachers of primary school in North Carolina to capture the students’ level of engagement in the class.

The researchers employed color and depth sensing cameras to identify where the students’ focused their gaze. Then, from the data collected, the teachers could find out if the students were attentive in the class. The education blog of Microsoft talks about how Tacoma Public Schools adopted predictive analytics which helped them improve their graduation rate from 55% in 2010 to 85% in 2016.

In a totally different field, meteorologists with the background of data sciences are using predictive models and machine learning to make accurate weather predictions. These examples show that professionals of any field can benefit from data science training.

You may love your job or hate it, but one trait of a career minded person is the zeal to learn. Learning is a continuous and life long process, as it should be. We learn a lot each day, on the job, in our personal lives, through our interactions and so on. But the prospect of learning a new skill may seem a bit daunting mid career, more so for a seasoned employee.

As a data science service provider, we at cross paths with a lot of passionate professionals who tackle most of their work challenges gracefully. Yet, a lot of them feel apprehensive or nervous about learning data science, most of their concerns clustering around the field being relatively new and so complex. Data science is not abstract or too difficult to understand, it can be an exciting learning experience if taught right too. We at FIO Labs have worked to make that feasible and convenient for you. Reach out to us to learn more.

THE FUTURE OF CAREERS IN DATA SCIENCE

Almost all of the big players in the industry like Google, Amazon, Microsoft, Walmart, eBay and Twitter are purely data-driven. Job opportunities for data scientists are booming.

A leading job portal, Indeed, records a 256% increase in data science jobs from December 2013. In 2018, 31% of the job postings on Indeed required data scientist job role. The same report notes that the salary of data scientist across the US is much higher than the average salary in those geographic areas.

Starting from the 1970s, the application of data science has expanded across every aspect of the industry and society. It is expected to grow in manifolds and expand its horizon into cutting edge fields like artificial intelligence and robotics.

Data science training helps an individual to stay on the top of the talent pool. For employed professionals, the training helps them become more productive, innovative and solve problems easily. Training in data science can also enable a person to bring social changes- it helps to improve lives, fight injustice and support democracy. In the era of information explosion, what is a better choice of career than being a data scientist?

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