Unfold the Mystery of Acquiring a Data Scientist Job Today

  • 2 weeks   ago
  • 118
Unfold the Mystery of Acquiring a Data Scientist Job Today

Well what was the job that Harvard labeled as the “sexiest job” of the century? Do I hear “data scientist?” You heard it right…it is data scientist. A data science job is tedious and challenging, one cannot simply become a data science professional overnight. It requires a certain set of skills and in-depth knowledge of the subject.
As described by DJ Patil, (Former Chief Data Scientist of the United States Office of Science and Technology Policy) a data scientist is that blend of skills that can both unlock the insights of data and tell a fantastic story via data.

Data Science: Definition
A data science field is a multi-disciplinary subject that entails the persons’ knowledge in subjects such as Mathematics, Statistics, Programming, and the use of tools and technologies to study and extract valuable data and provide valuable insights about the organization and the business.
To be precise it is the perfect combination of programming, analytical, plus business skills that allows extraction of meaningful insights from raw and unstructured data. With large amount of data being collected it is very important to understand that the companies will now be needing candidates skilled in various fields of data science such as data scientists, big data engineers and machine learning engineers to perform these tasks.
A data science career requires one to have extensive skills in mathematics, statistics, R and Python programming. Being a data scientist, one needs to take data, understand it, analyze it, and further be able to process it, extract value out of it and lastly be able to communicate the findings in a manner that is understandable to a layman.
Fastest growing job: How or Why?

 
  • Job roles such as data scientist, machine learning engineer and big data engineers were seen to top the list on LinkedIn’s top emerging jobs.
  • 11.5 million job roles to create by 2026 says U.S. Bureau of Labor Statistics and demand for data scientists to soar 28% by 2020.
  • Since 2013, there has been a job growth for data science professionals of around 344%. However, creation of new jobs will not stop globally.
  • Data scientists grows 6.5x times, as per LinkedIn’s emerging technology report.

Taking up a data science career can perhaps be one of the best choices today.
In the present market, hiring a data scientist isn’t restricted to simply large companies anymore. With the growing demand, almost every industry and organization are becoming data-driven. Thus, it is important that the candidates interested in data science can opt for a career in this field.
Data science today is being one of the job role that has grab quite the attention by techies. Having prior skills in data science is an added advantage. But, how will the beginners learn data science? What are the prerequisites required to become a data science professional today?

  • Statistics

Strong understanding in statistics is the key to data science. Simply put, mathematics, programming skills and software skills will not help you in anyways unless you don’t understand how to analyze a report without having strong knowledge in statistics. Every data scientists have their own set of skills and technologies that they prefer using, however when it comes to in-depth knowledge in statistics they all share a deep understanding.

  • Programming tools

It is the lingua franca of Data science is Python followed by R programming. Python dominates the data science world because of its large number of data analysis and data visualization libraries that is written in Python (NumPy, pandas, SciKit Learning, Matplotlib etc.). R is specifically used for statistical computing. It depends from a data scientist to another data scientist as to which language he would preferred working with. But being comfortable with both R and Python is an added advantage.

  • Machine Learning Algorithms

Machine learning is something by which one can teach the computer to perform tasks and learn tasks without being explicitly programmed. Machine learning techniques can be used to make decisions, make predictions based in the data that is being extracted and is applied in many fields of data science. A data scientist without machine learning skills is of no use to the company, since you won’t be able to tackle and solve a problem without knowing what the problem is.

  • Data visualization tools

Data science professionals will be required to work with a lot of data and this will be analyzed using excel. But apart from excel you also need to know tools such as Tableau, Rapid Miner etc. to share your results and insights in the form of graphs and charts and that can be easily understood by a non-technical individual or a stakeholder.

  • Predictive modeling

One needs to be able to build predictive models to predict the future behavior and for this you need to use machine learning techniques to identify the likelihood of the future outcome based on the data collected.
Learning these skills without a proper guide is not an easy task. Reason why IT professionals are moving towards re-skilling through online learning programs. The best way to fast-track one’s career.
The upward swing in data science will keep rising. An ideal way for one to grasp these skills quickly is by taking up credible certifications accredited globally. Some of the best data science certifications can be obtained through Data Science Council of America (DASCA), Hortonworks or IBM.

But will the supply-demand gap for data scientist diminish?

Comments