The amount of data generated today is astonishing. Research published by Seagate reports that by 2025, around 175 Zettabytes of data will be generated on an annual base. The colossal sets of collected, analyzed, monitored, and stored data is only increasing exponentially, and data scientists are in the midst of the process.
But in which industries data scientists belong to and where they can utilize their skills? Here is a list of some of the areas and functions where data scientists can reap endless rewards.
The financial industry is one of the most numbers-driven in the world, and one of the first industries that adopted data science into the field. As it is fairly known, financial companies are information-driven, and data science is the perfect helper to get actionable insights and obtain a sustainable development for financial institutions such as banks. Data science helps in risk assessment and monitoring, potential fraudulent behavior, payments, customer analysis, and experience, among many other utilizations. The ability to make data-driven decisions creates a more stable financial environment and data scientists make the backbone of the industry.
To see how to become a data scientist in the financial industry, you can explore the resource here.
By connecting pattern recognition, analytics, statistics, and deep learning algorithms, data science makes healthcare more efficient. The demand for data scientists in the healthcare area grows rapidly, according to research published by the Journal of the American Medical Informatics Association. The ability to quickly process large volumes of data for clinical and laboratory reports, data scientists enable a more precise diagnosis process by utilizing deep learning techniques. There are also many companies that market smart wearables, used to track and detect health conditions, and data science is in the heart of the process. This allows data scientists to reduce the risk of health issues, and directly impact the state of human wellbeing, not just in the US, but in the entire world.
3. Travel industry
Travel personalization has become an increasingly deeper process than it used to be. The possibility to create customer profiles based on segmentation, offering personalized experiences according to their needs and preferences, has its foundations in data science. At the graph below, we can see some of the main goals the travel industry has in its analytics programs:
Source: Eyefortravel research
This can offer an insight into the role data science has in the travel industry, and what is expected of data science on a strategic level. Forecasting the behavior of travelers by knowing where they want to go next, what kind of prices are they ready to pay, and when to launch special promotions, hugely depends on the level of applying data scientists‘ skills and abilities.
The energy industry experiences major fluctuations in prices and higher costs of projects – obtaining high-quality information has never been so important. Data scientists help in cutting costs, reducing risks, optimizing investments and improving equipment maintenance. They use predicting models to monitor compressors, which, in turn, can reduce the number of downtime days. „A day’s production at a small site – 1 000 barrels of oil – represents $30 000 of revenue,“ stated Francisco Sanchez, president of Houston Energy Data Science. Regarding the (data science) tools used in extracting and evaluating data, it can range from Oracle, Hadoop, NoSQL, Python, and various other software and solutions that can manipulate and analyze large datasets.
Often referred as industry 4.0 (with the introduction of robotization and automation as the 4th industrial revolution), the manufacturing industry keeps growing in need of data scientists where they can apply their knowledge of broad data management solutions through quality assurance, tracking defects, and increasing the quality of supplier relations. Similar to the energy industry, utilizing preventive maintenance to troubleshoot potential future equipment issues is another focus where data scientists can find good usage of their skills. Avoiding delays in the production process, implementing artificial intelligence and predictive analytics offers the possibility to manage frequent manufacturing issues: overproduction of products, logistics or inventory. In short, data scientists help in identifying inefficiencies and tuning the production process.
There are 2.5 billion gamers across the world, and the industry is becoming the heart of entertainment. Data science is used in the industry to build models, analyze optimization points, make predictions or identify patterns to ultimately improve gaming models. Not just limited to the production process, data scientists also work in the monetization, where they need to identify the most valuable players and analyze general consumer behavior to increase the profitability of the company (the more the players spend, the higher the profitability). Another area where data scientists can put their skills to use is in fraud detection; security levels in the gaming industry must be of highest standards, thus, machine learning algorithms allow faster identification of suspicious account activities.
Connected to human health, the pharma industry has also emerged as an industry where data science is increasing its application. For example, a pharmaceutical company can utilize data science to ensure a more stable approach for planning clinical trials. The patent exclusivity “starts roughly at the same time of its first clinical trial,” therefore, companies need to resort to data science in order to build precision into their calculations of the potential success or failure of the clinical trials. Another application can be seen before the trial even starts, by identifying suitable candidates based on their body structure such as chemical structure, medical history or other important characteristics. Data scientists read, evaluate, monitor and perform these analyses.
These are just some of the industries where we see active applications of data science and its benefits. The future will certainly bring even more usage of this exciting field, and, whether you are a striving data scientist or already in the field for years, the wealth of career choice is beneficial to all the inquisitive data explorers out there.