Nothing is more valuable in today’s world than data. You read it right – data! Not money, not gold, not cars, not assets but data. In this world, we are having around 3 quintillion bytes of data. And, it is a very tedious task to organize this humongous amount of data and churn information out of it. Data scientists blend entrepreneurship with perseverance, the urge to build data products continuously, the ability to explore and share, and the ability to iterate over a solution. They want to tackle and have to tackle every problem thrown at them- from data collection to data cleaning to predictions.
They have to think outside the box to come up with new ways to clear the problem or to work with very broadly defined problems.
According to Indiashoppers, they have to make most out of the zillion bytes of data which is thrown at them and take some meaningful out of it – term it as “information”. This is why we speak about Big Data and Data Analytics and it is the best career move to make in current times. Yes, it is written that “Data Scientist’ is the sexiest job title of the 21st century.” But, why is that?
Opportunities in Data Science Career
According to Harvard Business Review, “Data Scientist is a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data”. And, it comes with no surprise that why Data Scientists are hailed in the IT industry. Just imagine handling tons of data and analyzing and predicting some information and insights out of it which can bring a change in the world.
This is how the Data Scientist operates! To handle such data, there is a huge demand for data professionals. A study of McKinsey Global Institute held in 2018 stated that the USA alone will have a shortage of around 200,000 professionals with data analytical skills. This shows Big Data will not fade away and it will stay. Thanks to it, companies are running after data scientists and professionals.
Harl Varian one quotes that “The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades.” Believe it or not, data is the new intel under the hood.
Salary Trends for Data Scientists
As per a report by Glassdoor, Data Scientists will have the best package (in terms of money) and is the best job in the United States of America. With the median salary of $91,470 in the USA, there are thousands of openings on the site – just for data scientists. As per Indeed.com, an average Data Scientist salaries for job postings in the US are 80% higher than average salaries for all other job postings – as of May 2019. According to Payscale.com, the median salary of a Data Scientist is Rs. 622,162 – as of May 2019. From Google, Amazon to LinkedIn, from every big multi-billion dollar company to startups, every company is demanding data scientists and analysts.
Roles of Data Professionals
A data scientist’s job is not related to business analytics, building data products, making predictions, and creating interesting visuals and applying the code in machine learning algorithms to discover the pattern. There are many titles with a data scientist or a data enthusiast:
Some of the job titles of data professional are:
- Data Scientist
- Data Architect
- Data Administrator
- Data Analyst
- Business Analyst
- Data/Analytics Manager
- Business Intelligence Manager
A data scientist not only requires coding which can be blend with statistics. The ability to think critically and logically builds up the walls for a data scientist. Jeff Hammerbacher quoted, “… on any given day, a team member could author a multistage processing pipeline in Python, design a hypothesis test, perform a regression analysis over data samples with R, design and implement an algorithm for some data-intensive product or service in Hadoop, or communicate the results of our analyses to other members of the organization.” And, in those walls, a data scientist flies with his skills.
Some of the skills that are very demand-y and catchy for a data scientist’s perspective are programming languages like R, Python, and Java. Along with that Statistics and Applied Mathematics, knowledge of Hadoop and Spark, getting into SQL and NoSQL, Machine Learning and Neural Networks, and logical thinking can grab you some cashy jobs as Data Scientists. You can get detail of Off Campus Jobs online from fresh hiring