Top 8 Industries for Data Science Specialists in 2024

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Top Industries for Data Science Specialists

The field of data science has spread its presence everywhere. The broad scope of this multidisciplinary field has resulted in its numerous applications in almost all industries. According to Markets and Markets, the global market size of data science which was valued at US $95.3 billion in 2021 is projected to reach the value of USD 322.9 billion by 2026. The revenue forecast is expected to grow at a Compound Annual Growth Rate (CAGR) of 27.7%.

The demand for data science specialists is expected to rise by a staggering 28% by 2025 (Source: IBM Report). The aspiring candidate needs a comprehensive knowledge of the selected sector for their data science career. Here, we have enlisted the top 8 industries where data science is used.

  1. Oil and Gas

This is one of the best industries for data science with an incredible revenue of around $3 billion per day. In this industry, data science can be used for enhancing exploration, maximizing production rate, optimizing refining, improving marketing functioning, and comprehending consumer behavior.

Extracting detailed insights helps boost operations and decreases mistakes, thereby saving maintenance costs. To become a data scientist in this sector, you must have an essential technical skill set, knowledge of basic operations in this industry, and experience in implementing experiments and simulations.

  1. Healthcare

According to a report by McKinsey, technology-driven innovation in the healthcare sector is projected to produce $350 billion to $410 billion in annual value by 2025. It will help in ensuring customized and highly convenient care delivery and better patient understanding. From predictive testing, medical imaging, virtual assistance, anomalies detection in patient data to medical data privacy and patient engagement, data science has numerous applications in the healthcare sector.

  1. Insurance

The rising adoption of data science in decision-making and organizational processes is resulting in a high demand for data science specialists in the finance sector. Insurance companies are one of the examples of data science applications in finance. Data specialists working in insurance companies need to understand the basic terminology and the latest developments to easily perform risk modeling, lifetime value prediction, customer segmentation, and other tasks.   

  1. Agriculture

Data science implementation in agriculture is pioneering for farmers across the globe. Farmers are using data science technologies and concepts to increase crop production, enhance product quality, and decrease water usage.

Data scientists in agricultural companies are responsible for soil assessment, analyzing weather data, water management, food safety, crop forecasting, and precision farming. They could build data pipelines for scalability and automation, develop machine learning models, etc. To work in agriculture, data scientists need analytics expertise and domain knowledge.

  1. Cybersecurity

Cybersecurity involves avoiding global cybercrimes. Cybersecurity Ventures predicts global cybercrime costs to reach USD 10.5 trillion annually by 2025. Companies in the cybersecurity sector are hiring experts from the data science industry to prevent the rising use of algorithms for malicious activities. Data scientists use machine learning and AI to identify the source of these fraud activities and avoid their reoccurrence. They create models to collect data from pertinent cybersecurity sources and detect the data-driven patterns of these activities.

  1. Telecom

Most telecom executives believe that data analytics can contribute a lot to the future success of their company. According to Statista, data analytics is likely to unlock $1.2 trillion annually for the Telecom sector by 2025. The use of innovative technologies will produce more data that must be analyzed and managed effectively.

Every minute a huge amount of data is generated in the Telecommunication industry. For example, call details, customer information, and network details. Data analytics help telecom companies discover valuable insights, improve network performance, and boost their customer experience.

  1. Retail

The data analytics market size in the retail sector is projected to reach the value of US $18.33 billion by 2028, reported Global News Wire. Data analytics help retailers grow their business by tracking the value of their products, ensuring optimal pricing, and accepting relevant market challenges. Retailers across the world are hiring data science specialists to unlock insights from their customer journey, incentivize sales, anticipate supply chain disruption, predict demand and supply, and virtual applications.

  1. Big Tech Companies

According to SiliconANGLE, Wikibon, the revenue rate of the global big data market is projected to be $103 billion by 2027. The Big Five tech giants are the most trusted companies for professionals in the data science industry. Google, Apple, Amazon, Meta, and Netflix use data science for improved user experience, developing customized recommendation systems, and more applications.

Working in Big Tech companies is worthwhile because it not only provides a secure career and big salaries, but they are also at the leading edge of revolution. This is a reason why these companies are regarded as the top companies for data scientists.

Data science professionals in big tech firms work with different kinds of raw data, experiment with distinct algorithms and techniques, develop machine learning pipelines, handle, and store huge datasets, and collaborate with data scientists. So, to become a data scientist in these companies, you need a lot of hard work. You must understand statistics and mathematics, have expertise in programming language, proficiency in machine learning, and obtain a postgraduate degree in the relevant discipline.

Conclusion

These are the top industries you can choose for your rewarding career in the data science industry. Once you choose any industry, ensure you meet all the prerequisites for a specific job role. If you are just going to step into the field of data science, learn the basics, and get the required degrees. If you want to go ahead on your bright career path, develop expertise in the latest industry trends and advanced concepts, and earn well-recognized credentials.