Data-driven decision making is the need of the hour for every business these days. This means how we accumulate, disseminate, study, store, and act upon data will be the primary task for every data-driven organization. The value of the data science market is slated to reach $16 billion by 2025.
“Consumer data will be the biggest differentiator. Whoever unlocks the reams of data and uses it strategically will win.” – says Angela Ahrendts, ex-SVP – Retail, Apple Inc.
Such an upsurge in demand for data scientists is mainly because they can analyze structured and unstructured data to quickly and efficiently resolve problems that were previously possible with purely engineered solutions. Data science and AI technologies are being used for popular services like customer service chatbots at Bank of America, easy-to-search images on Facebook, and even automated fashion tips for clothing buyers of Amazon.
An increasing number of industries and domains are waiting to be disrupted and enhanced by data science methodologies.
Data science is witnessing a boom, which is the best time to pursue a career in this field. Data science skills are precious and applicable to companies as diverse as IBM, Amazon, Google, Netflix, Coca-Cola, Ford Motors, Starbucks, etc. Not to mention the countless not for profit and social endeavors aimed at building a better world.
Here are several industries worth exploring if you’re interested in using your data science and AI skills.
Increased numbers of use cases in the Banking, Financial Services, and Insurance (BFSI) sector have led to a massive increase in data to be analyzed and acted upon. The segment has mainly been integrating data science in all decision-making processes based on actionable insights from customer data.
There are many ways data science and AI can help financial institutions to be more efficient in providing services to their clients, some of which include –
- Fraud detection
- Lending and loan appraisal management
- Risk modeling
- Securing and managing customer data
- Lifetime value prediction
- Customer segmentation
- Algorithmic trading
- Underwriting and credit scoring
- JPMorgan Chase
- ICICI Bank
- Citi Group
- BNP Paribas
2. Media & Entertainment
The big players in the field of media and entertainment industry, including the likes of YouTube, Netflix, Hotstar, etc. have started applying data science to understand their customers and offer them the most relevant and customized recommendations. Even the regular entertainment channels and gossip newsfeed are relying heavily on user data.
A recent report by PwC suggests that India’s OTT video market will grow at a 21.8% CAGR from INR 4464Cr in 2018 to INR 11976Cr in 2023. Subscription video on demand will increase at a 23.3% CAGR from INR 3756Cr in 2018 to INR 10708Cr in 2023.
This new face of digital reality aims towards matching the personal preferences of the users and is evoked in the concept of addressability, along with the ability to interact with consumers as per their choices. In such a scenario where everything is dependent on data, the media and entertainment industry seeks data scientists who can collect, process, analyze, store, and provide recommendations, and make a desirable impact on the business.
Data science strategies, especially machine learning and artificial intelligence have scaled up the media and entertainment industry through –
- Customer sentiment analysis
- Hyper-Targeted Advertising
- Smart Recommendations & Personalized Content Experiences
- Real-time analytics
- Optimized Media Scheduling
- Programmatic Ad Buying
- Predictive Modelling for Targeted Content Generation
- Leveraging mobile and social media content
Fig – This graph shows consumer and advertising spend in digital and traditional channels across media and entertainment sectors including TV, film, music, gaming, books, magazines, and news.
Image Source – Forbes
- Dish Network
- Time Warner
- Hindustan Media
In the healthcare industry where most data is unstructured, and it isn’t easy to access and analyze all the data, hospitals and healthcare centers seek data scientists who can assemble fragmented heterogeneous data. From electronic medical records, clinical trials, and genetic information to billing, wearable data, care management databases, scientific articles, etc., data science has made it easier to manage all the information.
Data science has also contributed to designing and evaluating healthcare strategies that improve equity, opportunity, access, and health services quality.
Some of the areas with enormous scope for data science applicability, include –
- Drug Discovery
- Recognizing health risks and recommend prevention plans
- Diagnosis of diseases
- Delivering more precise prescriptions and customized care
- Post-Care Monitoring
- Hospital operations
While data scientists need to be proficient with programming languages and statistics, this sector requires professionals with “softer” skills like storytelling and excellent data communication skills to derive and communicate the desired results.
- GE Healthcare
Even the onslaught of the global pandemic, store closures, and layoffs couldn’t impact data scientists’ demand in the retail segment.
The consumer-focused retail industry thrives on increasing personalization and relevance, with one aim – to understand the shopper’s behavior and patterns through data.
Data science has helped retail businesses to ensure improved customer relevance, reduced customer churn, and larger basket sizes.
Retail businesses seek data scientists so actively because they bring a rare mix of strong data knowledge, business acumen, technology skills, intuition, and statistical expertise.
Data science in retail helps to –
- Analyze people’s past searches and purchases and help them find relevant products
- Create a recommendation and personalization system
- Analyze customer behavior and market insights
- Improve customer experience through predictive analytics
- Aditya Birla Fashion & Retail Ltd.
- Future Enterprises Ltd.
- Reliance Retail Ltd.
- K. Raheja Group (Shoppers’ Stop)
- Landmark Group (Lifestyle)
Now that subscribers consistently connect to telecommunications networks through voice, text messages, social media, etc., telecom providers have access to vast amounts of data. Other data sources, including website visits, past purchases, search patterns, and customer demographics like address, age, gender, and location, have proved to be crucial for the telecom businesses, and this is where the role of data science comes in.
Useful classification and utilization of this humongous data have been groundbreaking for telecom companies and have helped them cater to their more extensive range of consumers more accurately.
Data science enables telecom companies to –
- Make personalized offers to customers
- Allocate network resources
- Order predictive maintenance
- Ensure smarter network deployment
- Allow optimization and predictive maintenance of the networks
- Detect fraudulent activities
- Product innovation
- Contextualized location-based promotions
- Targeted campaigns
- Call Detail Record (CDR) analysis
- Optimized pricing
- Bharti Airtel Limited
- Reliance Jio
Data Science has helped the automotive industry to remain competitive by improving everything from research to design manufacturing to marketing processes. Moreover, the deployment of advanced analytics has led to the development of autonomous automotive systems such as sensors including cameras, radar, Global Navigation Satellite System (GNSS), Inertial Navigation System (INS), Light Detection and Ranging (LiDAR), and much more.
The role of data science in the automotive industry is not limited to –
- Enhance vehicle safety with cognitive IoT
- Decrease repair costs
- Create and manage schedules more effectively
- Improve production line performance
- Identify defects in produced components using predictive maintenance
- Enable manufacturers to gain greater control over their supply chains, including logistics and management
With automobiles getting more complex and capable of collecting more data, it was not possible to monitor wear and tear and report on mileage, fuel efficiency, and routes without data science. Be ready for the future cars that will communicate, collaborate, and navigate without human intervention! All thanks to the power of data.
- General Motors
- Maruti Suzuki
Almost every industry is trying to leverage the power of data to thrive in the market. If you are willing to pick the right data science skills, then probably you should consider picking a course that can help you grow in your career.
Our Course Recommendations –
Data Science for Engineers from IIT Madras on NPTEL (Duration – 8 weeks)
Executive Data Science Specialization by Coursera (Duration – 2 months)
The Data Scientist’s Toolbox by Johns Hopkins University via Coursera
Applied Data Science with Python Specialization by the University of Michigan on Coursera (Duration – 5 months)
Python for Data Science from IIT Madras on NPTEL (4 weeks)
Applied AI with DeepLearning by IBM on Coursera (Duration – 22 Hours)
With technology and globalization dominating the job markets today, data science will remain job relevant for years to come. If you have a penchant for patterns, numbers, and analytics, and have the right skill sets, data science is for you!