Data Scientist: The Most Popular Job of the 21st Century
Data Scientist touted to be “The Sexiest Job of the 21st Century” in 2012 by The Harvard Business Review, a little more than 10 years after the term coined in 2001! Come 2020, and we are facing a shortage of anywhere between 200,000-350,000 data scientists all over the world.
So, what exactly is a data scientist? What does he/she do? Do they have to be a real scientist with a Ph.D. degree? Well, let’s find out.
A data-scientist does not require formal college degree, rather the right set of skillsets. Based on the size of a company he/she may also take up the responsibilities of a data engineer, typically here are some of the must-haves:
- Coding and scripting knowledge
- A deep understanding of fundamental and advanced statistics
- Calculus and algebra
- Machine learning
- Data wrangling
- Data visualization and communication
Who Is A Data Scientist?
A company may require managers to plan products. Engineers to build them and marketing and advertising personnel to spread the word. You may also have other departments like operation and logistics based on the requirement. A data science team or a Data Scientist is not there to run your business. So why are they important? The answer is, to grow your business.
In the earlier days, every department used to conduct its work and, in the process, generate a lot of data. Unfortunately, this data was never passed on to other departments to take a look into. For example, say the marketing department receives negative feedback in its survey sheet regarding deliveries (which is not directly linked to the product). This information needs to reach the operations team but does not because of the lack of a data flow process.
A Data Scientist, if present, would analyze the structured and unstructured data produced by different departments of your company. They then enhance this data using information gathered from external sources and then build data models and make predictions and find hidden trends. These would then communicated to the entire company so that each department can use the information relevant to them to drive the product ahead.
Why Do You Need A Data Scientist?
Companies fetch data from multiple sources today. Data can be in the form of internal data generated by different teams based on their interactions with users. It can be system data — log files generated by the system that captures the activity of different users on your website. It can also be external data— competitor pricing data gathered through web-scraping. Data can also capture from various devices (using the Internet of Things) and appliances. Today almost anything you buy. Be it a fridge or a watch connected to the internet (read IoT). All this data needs cleaning, analyzing, and conversion to a format understood and absorbed by the business team. All of this taken care of by the Data Scientist. They not only take care of all the data sources at hand and communicate findings to all but also look into other sources to boost business and increase productivity.
There was a time when data meant excel-sheets. It’s consumed easily by the business team easily. Today, data has boomed and a very small percentage of that data is in a structured tabular format. Big data exists in semi-structured formats like JSON on XML and even in unstructured formats such as images, pdfs, videos, audio recordings, or plain text. While “plain text” may seem to be a good data source, breaking it into pieces and extracting information from it is a subject in itself, called NLP or natural language processing.
Understanding The Role Of A Data Scientist
Data science is the understanding of what a text means using code. Its knowledge is essential for data scientists who work on textual data. One of the common sources of data with all formats is social media — texts, images, videos, and more, all sitting together. With the new and varied data types that are not analyzed manually just by looking at the data. The business team is in a fix. The Data Scientist enables the business team to understand the data by converting it into a simpler format, breaking it down to understandable bits.
A pile of data is of no use unless worked upon. A Data Scientist uses the various tools at his/her disposal to understand the data first, and then uses data wrangling techniques to convert it to a workable format. Using this converted data, they usually create predictive-models. These models help the business team weigh different metrics against each other and find the optimum way to maximize business gains.
The Demand For Data Scientists?
The average base salary for a Data Scientist is $113000/year. And yes, that figure is higher than a Data Analyst or a Software Engineer. The reason, they are highly in demand. A Data Scientist needs to work on different stacks. He/ She needs to understand the questions that the business team needs answers for, from the data. He/ She needs to know coding and statistics to handle the data. And should have the infrastructure know how to make decisions based on which cloud infra to run an algorithm on. They also need to have visualization skills to know which is the best way to present the data and findings to the wider audience.
Since it is a highly specialized job title that requires a diverse skill set. It is understandable that the market has always faced a crunch of candidates. While the market has automated tools options, we still need data-scientists to use them. Today, the Fortune 500 companies have scooped up a large percentage of Data Scientists. The remaining have gone to well-funded startups. For the rest of the companies, there are a few fish in the pond and too many fishermen.
The Impact of COVID19
The current generations (Gen X, Y, and Z) have never experienced a pandemic before. And understandably we have no usable data from a previous one. This leads to an increase in the demand for Data Scientists. There is a requirement to simulate the circumstances and deduce consumer demand. Uncertain behavior, like high sale of paper tissues, can also lead to a decrease in sales later on, when everyone has a stockpile. Thus, market data needs analyzing in real-time today to best predict what tomorrow will bring. Even the spread of the virus itself being analyzed by Data Scientists to understand how fast-spreading and what are the means spreading through.
How Can You Become A Data Scientist?
A large percentage of data scientists who are working on data today were Software Engineers or Data Analysts, who learned the extra skills necessary through online courses or MOOCs on websites like Coursera and Udacity. There’s also a dedicated website, Kaggle, which has developed into the world’s large platform for Data Scientists and Machine Learning Engineers. Companies like Google and Lyft host competitions on the platform, where the team with the most optimized solution for a machine learning problem wins. There are also discussion boards, job-board, and more. All the resources that you may need are already there; you just need to take the leap.
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