Data scientist jobs come as one of the highest paid professions in the world, thanks to the rapid growth of data. After all, the LinkedIn report says that data science ranked as number 1. job in America. The data for the survey was taken from millions of member profiles on LinkedIn. The data included verticals such as salaries, job openings, ranking job roles, and career progression etc. This comes as no surprise in the tech sector that “data scientist” is still ranked the best job four years in a row, says a report by Glassdoor.
In 2020, IBM predicts the demand for data scientists is going to upsurge by 28% creating many job opportunities in the job market. Although, there is a rise in demand for data scientist professionals the demand outweighs the supply due to the shortage of talent.
As per the LinkedIn Workforce Report, it is found that there are more than 151,000 data scientists job role that is still lying vacant across the U.S. itself affecting cities such as San Francisco, Los Angeles, and New York City.
Big data, data science, and machine learning remain the most challenged technology skills to be filled in by professionals these days. Organizations are willing to pay lucrative salary packages to candidates with new-age skills. However, if these job roles are not being filled sooner, there will be a disruption in the job market.
Employers are in a massive lookout for candidates having skills such as critical reasoning, good problem-solving skills, basic coding skills, good aptitude, and communication skills. Although, most individuals may deny the fact that one does not need to be good with communication skills, however, is not true. As a data scientist, one needs to be good at communicating else how will a layman understand what analysis and prediction of data literally mean.
The main objective today is not “how one can get a job” but “what are the skills required” to get hired as a data scientist professional. There are certain ways that one can get hired as a data scientist today, but the conventional way is to first develop the skills. This can only be possible if one starts learning the skills that are needed to become a data scientist.
To do so, one needs to know the topics to learn as a priority. Let us try and filter out the major skills.
● Statistics and Statistical Analysis is the core foundation for data science, without this, one cannot further learn data science.
● Basic coding skills will be required to learn programming languages such as Python and R.
● Next comes, Machine Learning Algorithms such as Regression methods (Linear Regression, Logistic Regression), Random Forests, Bayes theorem and Naive Bayes etc.
● Predictive Analytics using Machine Learning algorithms
Theory knowledge comes in handy only when one will be able to solve real-world challenges in data science. Being a data scientist, your responsibilities include:
● Extraction and cleaning data using R and Python
● Analysis of data using Statistics and Statistical Analysis
● Present the findings in a simple and understandable format using Data Visualization tools such as Tableau, ggplot2, RapidMiner etc.
● Building predictive models using Machine Learning Algorithms. The most used machine learning algorithms are Decision Trees, Regression, Neural Networks, and other classifiers such as Clustering Algorithm, Time Series Algorithm, Factor Analysis, and Naive Bayes etc.
Data science is being used by almost all industries and organizations, but to get there one must have the skills. Getting into this field is tough without having the right set of tools and technologies. Most recruiters these days prefer candidates having certifications and credentials. Becoming a certified data scientist is a great way to stay ahead of a curve. But you need to ensure that one gets certified from an accredited resource since recruiters are quite specific when it comes to certifications and credentials. This comes handy when an employer hires a candidate, one needs to demonstrate the skills and tools and without demonstration, it gets very difficult for a recruiter to assess your skills.
To become a certified data scientist, you need to choose the right resource to learn them. The listing below are some great certification courses to ease your search.
● CAP - Certified Analytics Professional - This certification is for professionals who are already analytics practitioners. This certification is for organizations and professionals who further are seeking to enhance their credibility in this domain.
● DASCA - Data Science Council of America - The credentials offered by DASCA (Data Science Council of America) is one of the world’s inclusive coursework that offers the data science body of knowledge and data science essential framework. Anybody looking to start off their career in data science can learn from this platform.
● CCP - Cloudera Certified Professional - Professionals looking to earn a certification from this platform need to have in-depth knowledge and understanding in the data science field. The main objective of the training includes how to ingest data, understand what is data transformation, staging, and storage of data.