Data Science Career Fair


Data Scientists in the Healthcare Industry

By: Emil Moldovan – ODSC data science team contributor

Data science jobs are in high demand in healthcare. Don’t believe me? Talk to hiring managers from the healthcare companies Protenus, Metrum, CVS Health and Johnson & Johnson at ODSC East’s Data Science Career Fair to learn for yourself. In this post, we explore some of the roles that data scientists play in the healthcare industry.


Basic science is becoming a big data endeavor. Organizations such as MIT’s Broad Institute hire statisticians to advance basic science. Biologists produce datasets so large that data scientists have to step in to help.

Clinical research today also requires data scientists because they are ushering the era of personalized medicine(1). Personalized medicine combines genetic, behavioral, environmental, geolocation, biometric and social media data to paint a complex picture of a person’s medical condition.

Medical professionals use these profiles to predict the diseases people may contract, and to develop a treatment plan for them once they get sick. Each of these sources of data is complex, so piecing them together is a gargantuan task perfectly suited for data scientists.


As hospitals shift from fee-for-service to value-based payment systems, data scientists will be called to develop analytic tools(2) to improve the quality of service. Decision makers will want access to actionable data. For example, administrators use claims data to select cost-effective treatments, and eliminate unnecessary treatments(3). Hospital-wide data has epidemiological import because it can be used to spot disease trends faster than ever before. Doctors and nurses also like having access to patient summaries. Data scientists curate patient summaries with the latest visualization tools.

Companies such as Enlitic are developing better diagnosis tools for doctors using machine learning. Finally, natural language processing techniques will be used to collate information across multiple doctors that a patient has seen, to detect disease patterns that no single doctor would be able to spot(4).

Data Warehousing

In a recent survey, healthcare decision makers voiced concerns about the quality of data that hospitals are producing(5). You can’t do fancy analytics if you don’t have quality data to work from. HealthcareCatalyst published white paper(6) explaining that quality data warehousing needs to be developed before companies can put that data to internal uses (such as producing analytics reports for management) and external uses (such as reports for regulators and physician quality reporting systems).

There are a number of data warehousing issues that many hospitals have yet to resolve. Hospitals have yet to perfect their attribution systems. Attribution is the process of matching patient data with the right physician. Databases built in SQL and its extensions are often not well integrated. Unstructured data is not being queried with natural language processing. And protecting patient confidentiality remains a primary challenge for hospitals that want to share their data with outside sources.


Data scientists are stepping in to ensure that doctor’s prescriptions are honored. For example, the firm MedAware aims to use electronic medical records to detect possible prescription errors. Alme Health Coach promotes adherence to medication regimes via personalized alerts, and AiCure also notifies caretakers of poor adherence.

In sum, there are quite a lot of ways in which data scientists can make themselves useful to the healthcare world. Whether you are just finishing up school, or going through a career change, this is an excellent time to put your skills to good use.

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