Data Science Jobs that are set to be in demand in future – Times of India

By Anmol Mathur, VP & Head, Engineering & Technology

Businesses across industries have realized the importance of using data, which has led to a growing demand for data science professionals. Institutions, too, are providing learning solutions to upskill and upscale their workforce.

We are in a world driven by big data and estimated that by 2025, the volume of global data should touch 180 zettabytes. But this voluminous data will require domain experts who can convert it into actionable insights through advanced technology. Hence, the role of a data scientist is fundamental to support the leadership teams to formulate strategies and plans. Armed with the knowledge of subjects like statistics, mathematics and computer programming, data scientists leverage the power of technology to gain insights from reams of data businesses.

Globally, organisations have realised that data is the biggest asset they have collected over years of operation. However, they are unable to utilise it to its fullest potential. According to AIM Research, in India, there were 137,870 jobs in data science in June 2021 and witnessed a 47.1 per cent increase in open jobs requirement as compared to June 2020. India contributed to 9.4 per cent of the total global analytics job openings, a rise from 7.2 per cent in January 2020. In addition, recruitment services firm Michael Page India’s ‘The Humans of Data Science’ report revealed that data science will create roughly 11.5 million job openings by 2026. The LinkedIn’s Emerging Jobs Report ranked data science as the fastest growing globally and has witnessed a growth of over 650 per cent since 2012 and the market slated to grow from $37.9 billion in 2019 to $230.80 billion by 2026.

Data helps companies assess the market and consumer base that is becoming an indispensable asset today. With companies increasingly realising the true potential of data scientists, jobs in this field are expected to skyrocket. The US Bureau of Labor Statistics predicted that the rising importance of data science will lead to the creation of approximately 11.5 million job openings by 2026. These trends make it an opportune time to begin developing a career in data science. We enumerate a list of the most coveted jobs that will continue to drive demand in the years to come.

Data Scientist: Stemming from the conventional roles of statisticians, mathematicians, computer professionals, and data scientists are required to collect, analyse, and interpret vast amounts of data. They do this by using advanced technologies such as machine learning and predictive analysis. At big businesses, data scientists usually work in conjunction with a cohort of technology experts to mine big data and be eventually used by companies to predict customer behaviour and help identify new revenue streams. To work as a data scientist, candidates must possess high levels of efficiency in algorithm development, mathematics and statistics and a certificate programme in data science is considered beneficial.

Data Analyst: Data analysts use statistical tools and models to interpret large data sets to identify patterns that add value for businesses in making projections and predictions. Data analysts are known as ‘storytellers’ because they peer through massive amounts of data to identify common threads, patterns and anomalies that are not visible to others. From interpreting trends with the help of historical data to making data-based summary reports and developing data mining systems, the role of a data analyst is broad-based and includes interfacing with internal and external stakeholders.

Machine Learning Engineer: Machine learning and artificial intelligence are significant in their use for data science. With companies realising the importance of adopting technologies such as machine learning to anticipate customer needs, the demand for professionals is to rise. Machine learning entails a blend of two roles, namely data scientists and software engineers. Typically, a machine learning engineer helps to combine the complex analytical models created by data scientists with the skills of coders and programmers who design software systems. These spheres combine to create a synergy to help businesses leverage the full potential of AI and ML. Machine learning engineers work closely with data scientists to make sure that the models being used to interpret vast amounts of data in real-time can, indeed, generate the most accurate results.

Business Intelligence Developer: BI developers are essentially engineers for businesses who help interpret and display data for the key decision-makers in a company. They help with the compilation of data, and work to simplify valuable information for a company. A core function of their job is to create and maintain company software tools used to guide business strategies. Since BI developers also analyse complex databases, learners who want to make a career in this profession should have strong data mining skills. In addition, the knowledge of data warehouse design and Structured Query Language (SQL), a standardised programming language used to update and manage databases, is highly desirable.

Statistician: The role of a statistician varies depending on the industry or kind of company they are employed. However, they service companies to collect and interpret large amounts of data. Based on the data, statisticians help to point out current and emergent trends and even discover errors or discrepancies for company management to rectify. Statisticians can also be an advisor and share suggestions about organisational strategy. Hence, to succeed as a statistician, professionals need to exhibit effective communication, technical, analytical and leadership skills.

Data science incorporates a mix of theoretical and practical skills, and it is vastly relevant for diversifying businesses. As India aims to become a global hub for manufacturing, AI and related technologies, data science professionals are poised to play a pivotal role in helping businesses to generate actionable insights. To provide adequate skills to its learners, Times Professional Learning (TPL) has introduced programmes such as DATA JEDI. It provides a comprehensive set of Data Science, AI, ML, Deep Learning and Business Intelligence training to help create a future-ready workforce of highly skilled professionals in India.