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Five Great Specializations for a Master’s in Data Science

  • Statistical Analytics
  • Business Strategy
  • Cloud Computing
  • Marketing
  • Healthcare

Data science plays a role in every industry on the planet, from linguistics and marketing to healthcare and the arts. Forbes reports that data scientists have become much in demand, in both the public and private sectors and in non-profit and Fortune 500 companies alike. Here are five great specializations for a master’s in data science.

Related resource: 15 Most Affordable Master’s in Data Science Online

  1. Statistical Analytics

    Data scientists specializing in statistics carefully compile and analyze statistical data, use it to chart historical trends, and use it to make predictions about future occurrences. Statistical analytics specializations are useful in a wide variety of fields, including political science, meteorology, business, and finance.

    A specialization in statistical analytics involves strong mathematical skills and a sharp eye for detail in addition to the base skills of the data scientist. Statisticians may work alone or in teams with other data scientists depending on the scope of their project.

  2. Business Strategy

    This specialization involves the compilation and analysis of a wide range of data relating to business operations. From marketing and financial data to profits reports to stockholders and documentation, data scientists working in business have high-volume and broad-ranging duties for whichever companies they work with or for.

    Data scientists working in business may also be responsible for analyzing best business practices and history of success or failure with specific infrastructure and data management systems, and make recommendations based on this data for companies seeking to make an improvement to their practices and physical assets.

  3. Cloud Computing

    Cloud computing and Big Data are not just best friends, they’re siblings – and data scientists are more in demand than ever to manage cloud computing assets and analyze data that is stored within the cloud. In addition, data scientists working in cloud computing will also be expected to effectively computer system requirements for managing the cloud, executing and overseeing integration with applications and ease of access functions, and cloud system security.

  4. Marketing

    Marketing represents one of the largest sectors currently employing data scientists. From social media to online sales, record amounts of data are being produced every day relating to the marketing and sale of all kinds of goods and services.

    Data scientists working in marketing analyze this data to determine core demographics for companies, what methods of marketing are reaching the widest audiences, and which products or services are selling the most effectively. They use their findings to make recommendations to the company’s management team on which products and services should be receiving more focus, what should be discontinued on the basis of poor performance, and what parts of the populace should be the focus of marketing endeavors.

    Marketing also represents one of the most lucrative specializations for data scientists and is especially viable for data scientists who enjoy working in teams.

  5. Healthcare

    Data has become an indispensable part of effectively managing healthcare. Analysis of data can assist patients in receiving better quality care, more effectively managing hospital and medical campus budgets, indicate which areas of medicine require more research and investiture, and effectively quantify the staffing needs of medical institutions. Itself a highly lucrative specialization, data scientists are employed by hospitals, medical boards, and other healthcare institutions to provide high-quality information that can improve the lives of patients and medical staff alike.

These specializations offer unique opportunities within data science – and tremendous opportunities for growing and positively impacting a wide array of industries for years to come.


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