People associate data science with specific sectors like the tech industry. However, a Harvard Business Review (HBR) article notes that data science is “poised to transform all sectors.” Henderson State University offers a unique online Master of Business Administration (MBA) with a concentration in Data Science program. This degree program prepares students for success in any professional role dealing with big data.
Coursework delves into using information systems, data science and advanced big data analysis to drive effective, evidence-based business practices. This data science MBA also focuses on managerial skill development in communication and strategic decision-making — both essential for modern data science professionals’ success.
Because information analysis applies to nearly every industry, business skills regarding big data analytics and its applications are fundamental to numerous consultancy, management and specialized data science roles across a wide array of sectors. Here are five such industries for jobs dealing with big data:
1. Healthcare Technology
Data science professionals have helped develop technologies that can improve patient health outcomes and increase access to care while lowering costs. A prime example of this is the development of wearable technologies that can monitor health data.
As explained in a SAS blog, technologies like smartwatches and wearable sensors “enable patient data to be utilized by a physician via their real-time data tracking capabilities.” This feature facilitates remote monitoring and app-based treatment programs, reducing the cost, time commitment and barriers to accessing in-person monitoring programs.
Data scientists in various specialized roles are integral to the design and application of such technologies. On the research and development side, machine learning (ML) scientists and engineers develop and utilize advanced algorithms to gather and analyze health data via sensors. Specialists in data visualization and storytelling work with user interface designers to translate and represent data insights in understandable and engaging ways.
Outside consultants and/or a healthcare organization’s data science team implement health data monitoring and analytics systems and train medical professionals to use them. In such roles, data scientists rely on their technical expertise as well as communication, decision-making and leadership abilities. They are responsible for translating the insight data analysis offers and helping others develop the data-driven decision-making skills required to benefit from that insight.
Data science is also reshaping professional sports. Wearable technologies, sensors and video provide a wealth of real-time data on gameplay as well as athletes’ health and physical performance. ML technologies provide predictive and prescriptive analysis capabilities, which help teams optimize athlete training, health, safety, performance and gameplay strategy.
BigDataNomics calls this a “utopian scenario” for team managers. However, these technologies are only helpful when decision-makers can understand the story data tells. A sports organization’s data analytics team must organize information analysis and translate it into actionable insight for decision-makers through clear communication and visualization of essential metrics.
Video streaming services use ML algorithms to customize recommendations and personalize the user experience. Analysis of big data on viewership and movie-watching trends helps film companies determine what kinds of content to create and where to focus resources. Marketing strategies for movie releases are built off target audience data analysis.
ML engineers develop and continuously improve streaming algorithms. Data storytellers help directors and producers understand how to capitalize on current and future trends. Analytics professionals also help marketing strategists explore data using dashboards and other tools.
4. Hospitality and Travel
Data science has driven rapid evolution in many aspects of the hospitality and travel industries. Harvard Business Review mentions that data scientists are involved in product development for booking.com, and Airbnb uses ML to inform business decision-making. Big data helps such companies understand what people want from travel, including booking, hospitality experiences and activities during their trip.
Using algorithms, visualization tools and communication, data scientists help companies connect the dots between patterns in consumer behavior and customer feedback. This insight helps personalize and improve service offerings and the user experience from start to finish of a customer’s journey.
5. Law Enforcement
Law enforcement agencies have access to big data from myriad sources like social media, mobile devices, bodycam video and wearable devices. World Wide Technology (WWT) explains how advanced AI and ML algorithms can rapidly analyze law enforcement data aggregated from disparate sources and siloed data repositories. This analysis generates “deeper and therefore accurate predictive insights about myriad community situations.”
A Security Distillery article concurs that AI “offers the field of law enforcement an incredible opportunity to better prevent crime.” The report also points out privacy concerns and potential bias inherent to ML-driven preventative policing. As a result, ethical and legal conversations have spurred the development of another data science specialization: the data ethicist.
Modern data science impacts industries of all types. Advanced technologies can automate many mundane tasks of traditional data science, prompting the development of specialized technical and interpersonal roles in the field. With a combination of data science expertise and honed managerial skills, data-driven professionals can pursue a vast range of truly unique career opportunities.