Data Scientist identifies trends, patterns, and anomalies found in big data sets by performing extensive data analysis to develop insights. Performs data mining, cleaning, and aggregation processes to prepare data, implement data models, conduct analysis, and develop databases. Being a Data Scientist interprets results from multiple structured and unstructured data sources using programming, statistical, and analytical techniques and tools. Collaborates with teams to understand each data analysis projects' underlying purpose, focus, and objectives. Additionally, Data Scientist designs, develops, and implements the most valuable data-driven solutions for the organization. May require a master's degree in computer science, mathematics, engineering or equivalent. Typically reports to a manager. The Data Scientist work is closely managed. Works on projects/matters of limited complexity in a support role. To be a Data Scientist typically requires 0-2 years of related experience. (Copyright 2024 Salary.com)
Under the direction of Dr. Shaban-Nejad, the Postdoctoral Fellow will be responsible for Cancer data analytics, statistical modeling, developing machine learning algorithms and models, geocoding, and visualization of the proposed framework.
The successful candidate will work with a team of experts led by Dr. Arash Shaban-Nejad and David Schwartz on cancer data analysis, data management and governance, statistical and epidemiological inference and causal modeling and implementing machine learning solutions to enhance cancer surveillance and control and improve equity in cancer care and outcomes.
Duties:
·Integrating and analyzing clinical and social determinants of health datasets
·Designing, implementing and applying analytical solutions and advanced statistical methods, discovering patterns and generating actionable insights and recommendations
·Developing and utilizing Machine learning (ML) algorithms, as well as statistical and other predictive models to guide and recommend actions for improving cancer care and reducing health disparities.
·Working closely with a diverse team of experts towards creating and utilizing an AI based platform to improve cancer care
·Training students and junior researchers throughout the project life cycle
·Writing reports, manuscripts and articles to appear in top journals and conferences in the field
·Participating in proposal preparation and research for national and local grant agencies
Qualifications
Ph.D. in a relevant discipline (e.g. Computer Science, Software Engineering, Medical Informatics, Mathematics, biostatistics, etc). Strong track record of quantitative and analytics mastery, and expertise in Statistical analysis, Machine Learning, Causal Modeling, and Epidemiological studies; Outstanding interpersonal skills and written and verbal communication capabilities.
Experience in Trustworthy AI, Knowledge Representation, Statistical Modeling and Casual Inference
Applicants should have a demonstrated commitment to and knowledge of equal employment opportunity and affirmative action.
The University of Tennessee Health Science Center is the flagship statewide, public, academic health institution in Tennessee. Founded in 1911, the mission of the University of Tennessee Health Science Center is to improve the health and well-being of Tennesseans and the global community by fostering integrated, collaborative, and inclusive education, research, scientific discovery, clinical care, and public service. Employing more than 4,600 people on its faculty, staff, and not-for-profit corporation faculty practice groups, and with more than 3,200 students across the state, UTHSC contributes $4 billion to the economy of Tennessee.