In this data-obsessed world, data scientists have appeared as the most demanding commodity. The hunt is on to find the best genius in data science. Already, experts have evaluated millions of jobs in data science that are vacant due to inadequate talent and knowledge among the candidates.
The all-around search for skilled data scientists is not solely the search for a statistician or computer scientist. As a matter of fact, the companies are searching for an all-around candidate who holds subject proficiency, has some experience in software programming, analytics, 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. Companies are going to struggle, employing millions of new workers to operate in this digital world. That's why Harvard business school said data science is " the sexiest job in the 21st century”.
A survey shows that “In 2018, the US alone could face a scarcity of around 140,000 to 190,000 of employees with deep analytics expertise, as well as a million managers lacking the expertise of using big data analytics to make compelling decisions. As the digital transformation has affected different aspects of our life, the benefits from self-learning about our digital presence and behavior are so much more now than back in time. Delivered the right data, marketers can gain deep insight into our habits.
When firms appoint 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've mastered the amazing art of storytelling. I think what one must do is to see, given the bunch of applications you have, who has the most seniority with your firm's background. This is because you can give training in analytics skills, anyone can be trained in analytics skills if they commit time and intent to it. However, what's really important is who's passionate about the craft they 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. However, 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 growth.
Data scientists have good mathematics and statistics history. They are considered to have problem-solving skills and analysis. The scientist needs to be excellent in analyzing problems. The candidate they are enlisting should love to play with data. This way, they know how to gracefully work with data visualization.
They must have the skill to present a 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 you have a great conclusion, presented well, this is what other people experience because they were not predicting it. They were not familiar with it, and they feel this great sense of achievement. It encourages them and gives them a concept about what they can do with this insight. It's an enormous joy, and you are a good data scientist, ready to share information with your clients because you empowered it.