In this data-obsessed world, data scientists have appeared as a most demanding commodity. The hunt is to find the best genius in data science. Already, experts evaluated a million of jobs in data science that are vacant due to inadequate talent and knowledge in data science among the candidates.
The all-around search for a skilled data scientist is not solely the search of statistician or computer scientist. As a matter of fact, the companies are exploring all-rounder candidate who holds the subject proficiency, have some experience in software programming and analytics as well, and phenomenal communication skills.
Our digital imprint has evolved and enlarged in the past 10 years. By 2020, our digital footprint has an expected size of 40 trillion gigabytes. The companies are going to struggle for not only thousands but millions of new employees to operate in this digital world. That’s why no exclamation why Harvard business school said data science as “Sexiest job in the 21st Century”.
Some statistics on Data Science:
A survey shows that “In 2018, the US alone could face a scarcity of around 140,000 to 190,000 of an employee with deep analytics expertise as well as a million manager and managers with the expertise of using big data analytics to make compelling decisions.
As the digital transformation has affected different aspects of our life, the idea and convenience to benefit from self-learning about our digital presence and behaviour are more so now than back in time. Delivered the right data, marketers can take a deep crawl into our habit insight.
When the firms are appointing people for a data science team, maybe a data scientist or an analyst, or a chief data scientist, the drift would be to search the candidate who has all the talent, and they know the domain-distinct expertise. They’re fabulous in analyzing structured and unstructured data. And they’re immense at offering and they’ve got amazing storytelling art.
I think what one must do is to see, given the bunch of applications you have, who has the most sonority with your firm’s background. Because you can give training in analytics skills, anyone can be trained in analytics skills if they commit time and intent to it. But what is really important is who’s passionate about the craft you do.
Someone could be a tremendous data scientist in the retail environment, but they may not be enthusiasts when they are working in IT-related companies or working with bytes of web content. But if someone is enthusiastic about those weblogs, if someone is keen about health-related data then they would be willing to commit to work and to your fertility much more.
What a Data Science professional is like:
The data scientist has a good mathematics and statistics history. They are considered to have like problem-solving skills and analysis. The scientist needs to be excellent in analyzing problems. The candidate they are enlisting, they should love to play with data. And then they know how to gracefully work with the data visualization.
So the skill to present your conclusion, either verbally, or in a presentation, or in a document. So those communication and demonstration skills are equally valuable as compared to the technical skills.
So when you present your data and conclusion and you have this great finding and you present it well, this is what other people experience because they were not predicting it. They were not familiar with it, and then this great sense of achievement that I now know. And then it encourages them, it gives them a concept about what they can do with this insight. It’s an enormous joy. And you are good as a data scientist, you are ready to share with your clients because you empowered it.
Blogging is a way of sharing creativity and knowledge which makes me enthusiastic and keen to new experiences.