20 Jul 2021 19:02 IST

Data science field brimming with promising opportunities

A look at some key jobs for data science professionals and the basic skills they must possess

Data is the new currency in today's world. It is among the paramount factors, along with emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML), driving the digital transformation of businesses across industries. Around 2.5 quintillion bytes of data get generated daily. Every organisation worldwide is looking for ways to capture this vast data volume and leverage it to stay ahead in the competitive market. In other words, we're witnessing the rise of data-greed. A NewVantage Partners' report shows that the number of organisations investing more than $50 million in Big Data and AI initiatives rose to 64.8 per cent over the last year.

Working with an enormous amount of data and deriving useful insights from it is becoming the most sought-after skillset in the market. Companies are actively looking for skilled data science specialists to join their teams. As of today, there are more than 22,000 data science job roles vacant in the country on LinkedIn alone. There is no better time for aspirants to consider building a career in this domain.

In terms of job outlook, data science specialists are among the top 15 LinkedIn jobs in 2021. Not only is it among the hottest professions of the year in terms of job satisfaction, but also a field that offers lucrative packages. An early-career data scientist, with or without experience, earns ₹5 lakh to ₹7 lakh annually. If you're passionate about data and love to play with it, a career in this field is your ticket to building a promising career.

Here are a few of the most popular data science job roles you can consider as a career path in today’s market.

Data analyst

They work with large data sets and are responsible for manipulating them for the necessary analysis as per business goals. Their work influences various business decisions, from marketing to finance. Their key responsibilities also include monitoring and coordinating the A/B tests for an organisation. Data analysts leverage A/B testing in data science to optimise better user experience

Data engineer

It is the data engineers’ responsibility to create a framework upon which data scientists and analysts work. This means that they are responsible for creating the infrastructure by generating for the recording, viewing, and reviewing data. Large-scale databases and processing systems are designed and managed by data engineers so that other staff in their company can use these systems to uncover patterns and draw conclusions.

Data scientist

They accumulate complex data and derive insights for the easy understanding of all stakeholders involved. More than just research and analysis, they're in charge of all things involving data, including arranging it and making it available, then drawing concrete trends and patterns from the data.

Data architect

They are responsible for developing data solutions and designing analytics applications for various platforms. Their key responsibilities include exploring ways to enhance the efficiency and functionality of existing systems, creating new database systems, as well as working to provide access to database managers and analysts.

There is a path for you to pursue a data science career, irrespective of your prior experience. But it requires skills, a thirst for knowledge, and patience to build a successful career in the domain.

Here are a few pre-requisite skills that will get you hired in this field:

Programming skills

Data science professionals are expected to have a good command over statistical programming languages, like R or Python, and a database querying language like SQL.

Statistics and probability

When you start writing, you need to be familiar with grammar to construct the right phrases. In the same way, knowing statistics and probability is a must for a data science professional. Understanding the definition of descriptive statistics is a must — mean, median, mode, variance, and standard deviation — for creating effective models.

Data visualisation

It is imperative to visualise and communicate data, particularly with companies where data science professionals are seen as people helping others make data-driven decisions. This includes explaining insights and how strategies work with viewers, to both experienced professionals and novices.

Communication skills

Formulating the problem statement is an indispensable quality of an expert data science specialist. At the beginning of every project, the stakeholders communicate to the data science specialist the requirement, and then the latter formulate a problem statement. Data science professionals must be able to articulate how insights can help them boost the company's revenue.

Learners can acquire proficiency in these skills by pursuing a certification course in data science. Jigsaw Academy offers a placement-guaranteed Postgraduate Diploma In Data Science programme, in collaboration with Manipal Academy of Higher Education (MAHE), a perfect blend of data science and emerging technologies.

Halappa Guruppanavar, Data Scientist, Healthcare and BFSI at Tata Consultancy Services, shares his career transformation journey. He says: “As a BBM Graduate, I had almost accepted that I could never get into analytics. The Postgraduate Diploma programme didn't just help me get my dream job but also enabled me to get a 110 per cent salary hike.”

(The writer is COO & Co-founder, Jigsaw Academy)