3 Skills Required for Non-Tech Professionals to Pursue Data Science

Data science career for non-tech professionals

The above skills are a basic requirement to be a data scientist. However, since data science and big data analytics are new disciplines, there is no fixed pathway to becoming a data scientist. The truth is that data science is multi-disciplinary. For example, someone with a finance background can be a tremendous asset to the company as their ease with numbers and business gives them an edge in understanding the business operations and the financial health of companies.

Less than half the people end up working in fields where they hold a degree in. It can be an onerous task to become a data scientist, but not an impossible one. If you are passionate about working with numbers, have an analytical mind, and possess the qualities above, then hard work, perseverance and a relentless drive will get you to your goal.

Find the data science ‘niche’ you want to specialize in and pursue the training and education for it. There are innumerable courses that give you the necessary theoretical knowledge you need. Jigsaw Academy, for one, offers customized programs across various levels and is designed specifically for industries and domains where such talent is in demand.

Backed by their success in skilling and upskilling employees in the BFSI and IT/ITeS sectors, Jigsaw Academy is now well-equipped with the right academic and industry resources to train learners to become future data scientists, data and business analysts, data engineers and data visualizers.

Jobs in data analytics have repeatedly appeared on various lists as one of the best jobs of the future. No wonder people from various disciplines are making the shift in their learning pursuits to become Data scientists. The question though is, can those from non-tech backgrounds also pursue data sciences?

Let’s talk about some of the behavioural or non-tech skills needed to be a data scientist:

1. Business acumen

It is not sufficient to have an understanding of Python or Hadoop. You have to be able to discern how your skills can be used to determine the problem or solve the problem that your organization is facing in its industry. A data scientist isn’t just technically-equipped, but also has to be street-smart to understand the industry and identify new ways to leverage its data to get ahead.

2. Intellectual curiosity

Solving a problem is not a task for a data scientist, but an intellectually stimulating journey. These professionals are not driven by money, their motivation is to be able to use their creativity and ingenuity to solve tough problems as they indulge in intense intellectual curiosity. It is an important trait or mindset to succeed as a data scientist, as they uncover the hidden meaning behind an indiscernible amount of information.

3. Communication skills

It is important for a data scientist to be able to clearly and fluently engage in conversations with members of non-technical teams to be able to communicate their technical findings. Only with strong communication skills, can a data scientist enable businesses to make logical decisions that are backed by quantified data.

So go ahead, start on it and become part of the ‘next big thing’. To find out more about our courses, click here.