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As technology in the modern business environment continues to evolve, IT roles in the workplace will need to adjust to the new demands to stay relevant. While this holds true for all technology roles such as developers, coders, and others, the demands placed on data science positions are more exacting. Why? Data analysis is quickly becoming the backbone of every business activity, powering superior decision-making and competitive differentiation.
By 2025, data analytics skills will be as important to everyday work life as functional Microsoft Office skills are today. According to The Quant Crunch 2017 report, the number of data-related jobs in the United States alone will increase to 2.7 million by 2020. The number of jobs in India is likely to increase much faster, as compared to the rest of the world, as more analytics projects get outsourced to India – to not only tap into scarce data analytical skills but also leverage cost-benefit advantages.
Let’s deep dive into the data analytical skills that three key industries will need to thrive in the future and how they can future-proof their data analytics workforce:
Skill requirements for tomorrow’s data scientists: IT, Retail and Banking
Technologies such as Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Blockchain, and Internet of Things (IoT) were considered niche skills until a few years ago. They are now shedding the tag by going mainstream. In 2018, the Indian industry is expected to add between 180,000 and 200,000 new jobs (from large services companies as well as start-ups), mostly related to these new technologies. Businesses are looking to create tangible, real-life impact with data and these technologies serve as critical enablers in achieving the goal.
#1 Information technology: Convergence of skills and capabilities will be the new way forward in the IT industry. The industry will need a new breed of data science professionals who understand development, data and analytics, machine learning and AI. According to CompTIA’s 2018 IT Industry Outlook report, emerging job roles include machine learning trainer/scientist, AI developer, industrial IoT engineer, blockchain developer/engineer and robotics engineer. Another significant area where more positions will be created is in supporting recommender systems — applications that use data to produce recommendations and options for users - a la Amazon’s product recommendation engine. Forward looking organisations are already preparing to lead the disruption. Tata Consultancy Services (TCS) for instance, has recently trained over 200,000 of its data science employees in AI and IoT.
#2 Retail and eCommerce: As omni-channel becomes the new norm, retailers are scrambling to incorporate a number of new and different sales channels to match customer expectations, leading to shrinking profit margins. These pressures are leading to a greater focus on workforce productivity. Savvy retailers are looking to train employees in emerging technologies such as RPA, IoT sensors, AI, and others to provide a personalized shopping experience. Flipkart has recently launched an AI for India initiative wherein the company plans to use its decade-strong customer data coupled with an AI platform to get a leg-up on its competitor – Amazon, in the Indian eCommerce market. Similarly, luxury fashion portal Net-a-Porter is investing heavily in data and technology and is one of the first in the world to introduce ‘Cognitive Fashion’ – a true blend of luxury and tech.
#3 Banking: The digital talent gap stands at 62% in the banking industry – the highest among several sectors such as retail, consumer products, automotive, and telecom. It’s clear that future-proofing banking talent is a pressing need. 30% of banking employees feel their current skill set is redundant now or will be in the next one–two years. Banks need to provide advanced technical (AI, ML, RPA, Blockchain, and IoT related) as well as soft-skills training to employees to help them stay relevant in the digital age. Innovative banks are also partnering with educational institutions to create a robust ‘talent bank’ and ensure that employees are job-ready from day one.
Create tomorrow’s workforce today
To meet the demands of tomorrow’s business landscape, organizations must start preparing today. While up-skilling your data analytics workforce in AI, ML, and IoT skills should be a key part of the talent development strategy, data science professionals must also acquire a business perspective – i.e. keep a finger on the pulse of the business/customers, solutions, competition, and costs. After all, at the end of the day, the sole purpose of leveraging data is to make the business better, more profitable, and sustainable.