The use of Big Data and it’s applications in Artificial Intelligence and Machine Learning, have led to the rise in demand for data scientists at an unprecedented level across all major industries. Both small and large oranisations are relying on the technical knowhow of data scientists to grow and sustain. Apart from hiring people, these companies are also organising data-analysis-focused programs to get their employees well versed with data handling and analysis.
A job as a data scientist is one of the most promising and well paid jobs of current times, with great job satisfaction and a huge potential for growth. But these perks have to be earned by data scientists.
The position offers a lot of challenges, which are diverse in type and complexity, and calls for expertise which can efficiently handle those varied challenges. It may require executing of a complex database query, or interacting comfortably with other data handlers, users and producers.
In order to be successful as a data scientist, one needs to master a balanced mix of both hard and soft skills. Here we are going to discuss the top skills that data scientists need to master in order to get the job of their choice.
Data-centric problem solving skills.
A data scientist’s productive approach to solving a problems helps to achieve the desired results. A data scientist must be able to identify the features of the problem, and then know which approximations or which set of people would do the magic. He should precisely know which data science methods when applied would work and which would not.
A sound knowledge of computer languages
Data scientists generally use a variety of software packages and programming languages to effectively extract and analyse the data at hand. In order to execute the processes, he must know about the tools of the trade in good depth. Expertise in a statistic based programming language such as Python or R, and a software used for database management systems such as SQL (Structured Query Language) would definitely come in handy.
Statistical analysis skills
Nowdays, there are many softwares which are in place for running the necessary statistical tests. Even then, a good data scientist is expected to have the statistical sensibility which is required in order to ascertain the test to run in a particular situation and be able to analyse the results of the tests.
Ability to work with unstructured data
The data that comes to an organisation from various channels is often highly unstructured and disorganised.
These unstructured data are content that are undefined and often cannot be put into database tables – social media posts ,customer reviews, video and audio feeds etc.
It is very difficult to sort these as they are not streamlined, and therefore are often referred to as ‘dark analytics’ because of their complexity. A skilled data scientist should be able to work with unstructured data to provide useful insights which are crucial for decision making.
Excellent communication skills
Autoregression and Bootstrap Averaging – these terms are a piece of cake for data scentists, but may sound like horror movie titles to the common man. So a skilled data scientist must invariably possess good communication skills to be able to fluently and clearly translate their technical findings and reports to a team which is non-technical in nature such as the sales or the marketing team. They should also be receptive to clearly understand the expectations of the non-technical team so as to be able to wrangle the data more appropriately.
Becoming a data scientist is a challenging task because of the above and many more skill sets that they require to possess. This is the reason why they are valued so much in the industry.
In your quest to becoming an expert data scientist and landing your dream job, it is highly advisable to first brush up the things you already know, before building up on them and learning new skills which would increase your chances phenomenally.