Demand for data scientists is surging

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Demand for data scientists is surging

Data scientists have been consistently ranked among top professions for the 21st century. Data scientist ranks third on Glassdoor’s list of best jobs in America 2020 and third on Linkedin’s emerging jobs in 2020. 

 The world is creating 2.5 quintillion bytes of data every day, the increasing demand for data scientists is justified. Data-driven business strategies are the first Amid all this, a data science career is nothing less than promising.  

Who are hiring data scientists? 

Nearly all tech companies are hiring data scientists. The prominent companies, however, have the most data scientists on board. According to Tech Republic, the following companies have the most data scientist according to the Tech Republic- 

  • IBM (2,563 data workers) 
  • Amazon (1,846 data workers) 
  • Microsoft (1,800 data workers) 
  • Facebook (1,220 data workers) 
  • Oracle (1,210 data workers) 
  • Google (904 data workers) 
  • Apple (568 data workers)

As is inevitable, the U.S has more data science professionals than anywhere in the world. Tech republic suggests the U.S, India, and the U.K has nearly 152,068, 27,602, and 16,106 data science professionals respectively, followed by France that has 10,297 data professionals.  

 What do data scientists do? 

Data scientists are problem solvers who help businesses solve problems using data. They require proficiency in statistics, R and Python programming, machine learning, discrete mathematics, and more. 

 A data scientist role can be summarized in the following steps — 

 1. Data collection – Data collection is a large part of a data scientist’s work. They collect data from various sources. 

 2. Data analysis – They perform data analysis using various statistical techniques to uncover patterns and figure out the relationship among various factors that are responsible for the success of a process. 

 3. Data visualization – Present analysis data to stakeholders to convey findings. 

 4. Modeling – Build machine learning models to predict outcomes of existing business processes, so preventive or progressive measures can be taken. 

Data scientist, however, isn’t the only role that has gained prominence in these years. Several other roles have gained an equally prominent role in the data science space. The following roles are predominant in the field of data science. 

 1. Data Analyst

 2. Data Engineer 

 3. Data Architect 

 4. Machine Learning Engineer 

 4. Business Intelligence Engineer 

 How to learn data science? 

Data science is a multi-disciplinary domain and requires extensive learning. University and colleges offer a full-time master’s degree in data science. These are good options for people who are looking to start data science from scratch. Additionally, Ph.D. programs in data science are common among professionals who are looking to accelerate their progress in data science. University of California, Berkeley, University of Missouri, Columbia, and Columbia University offers the world’s leading data science programs. 

 Data science certifications are equally prominent among fresh graduates and seasoned professionals to learn and validate their skills and move ahead in their careers. IBM, DASCA, Cloudera, are a few organizations that offer valuable industry-recognized certifications. Here are some prominent globally-recognized best data science certifications for professionals. 

 1. Associate Big Data Analyst (ABDA) – This certification is offered by DASCA (Data Science Council of America) for fresh graduates who are keen on starting a data science career. This certification demonstrates the candidates’ skills in Big Data tools including Hadoop, Flume, Pig, and more, and shows readiness for a data analyst role. 

 2. Senior Associate Business Data Analyst (SBDA) – This certification is a level-up from ABDA and prepares you for an advanced data analyst role. Experienced data analysts can further expand their skill set and head towards a more progressive path. SBDA demonstrates your advanced skills in Big Data tools and analytics using R. Plus, your excellence in using Python for data science.  

 3. Cloudera Certified Associate – Data Analyst (CCA) – This certification is offered by Cloudera, a leading software provider for enterprises. CCA prepares candidates to work on Cloudera’s proprietary cloud management software. CCA demonstrates the holder’s expertise in SQL and the ability to work in the CDH environment. 

 4. IBM Data Science Professional Certificate 

This is a professional certification offered by IBM in collaboration with Coursera. This certification equips aspirants with a vast range of data science skills including data analysis, visualization, machine learning and more. Further, the certification offers candidates hands-on assignments using IBM Cloud dataset, which ultimately leads to candidate building a portfolio of data science projects.

5. Dell EMC Proven Professional (Data Science Associate)
This is a beginner level certification that prepares you for an entry-level role in data science and to effectively participate in big data and analytics projects. You learn data analytics lifecycle, data analysis using R, data interpretation, and advanced analytics using techniques such as clustering, regression analysis, decision trees, Naïve Bayes, and more. The certification also preparesyou for advanced Big Data analytics tools.

All in all, demand for data science professionals is on the rise. Above are a few ways to learn data science, choose a path that you’re most comfortable with and carve a new career path to the hottest job of the 21st century!   

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