On a daily basis the candidate may be required to extend knowledge in the application of data analysis and predictive modeling to common healthcare datatypes and outcomes. Qualified candidates should have demonstrated experience in developing statistical analysis plans, applying Bayesian statistical methods, classical parametric modelling, and contemporary data driven approaches, including generalized linear and nonlinear approaches, to predict clinical outcomes from health records and administrative claims data, and preparing summary reports and presentations for relevant stakeholders. Special consideration will be given for direct experience in identifying, analyzing, and predicting hospital readmission events as defined and described in CMS’s Hospital Readmissions Reduction Program (HRRP).
Healthcare Data Scientist Responsibilities: Performing relevant literature searches and developing hypothesis driven analytic plans; Compiling and organizing healthcare data, including electronic health records, ICD diagnosis, procedural, and pharmacy claims data, laboratory results data, and patient demographic data; Designing, developing, and deploying predictive statistical models using healthcare data to predict relevant clinical and administrative outcomes in a secure and scalable environment; Collaborating with clinical and administrative teams to define business objectives and tailor analysis to measurable and durable performance metrics; Contributing to final predictive modeling recommendations and disseminating results to relevant stakeholders.
Master’s degree in mathematics, statistics, data science, engineering, or related field, along with experience in a statistical analytics role; or bachelor’s degree in mathematics, statistics, data science, engineering, or related field, along with experience in a data science or statistical analytics role.
Knowledge of big data platforms and tools, including parallel computing frameworks such as Apache Spark and CUDA
Knowledge and experience in cloud computing platforms, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP)
Expertise with relational databases and querying languages such as SQL;
Proficiency with statistical programming languages SAS, R, and Python for data manipulation, analysis, and predictive modeling
Knowledge and experience applying classical frequentist and Bayesian methods, data driven machine learning, deep learning, and AI techniques, combined with sensitivity analyses and evaluation techniques
Health data domain expertise required, including knowledge and experience working with EHR data, administrative claims data, and health economic data
Data visualization experience and presentation skills required; Experience with software engineering best practices, including git version control for source code management, automated testing and CI/CD, and agile development;
Excellent written and verbal communication skills
Excellent interpersonal skills
Excellent critical thinking skills
Leadership and visionary abilities preferred.
Commensurate with experience
The successful candidate will be required to have a criminal conviction check.
About Virginia Tech
Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.
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