Data Science Director establishes, plans, and administers the overall policies and goals of the data science function. Provides strategic guidance and overall direction for analytical efforts. Being a Data Science Director determines the appropriate tools, techniques, staffing and methodologies to extract data that produces meaningful results. Uses extensive knowledge and research into big data tools to guide the integration of new and existing tools into the organization's data science tech stack. Additionally, Data Science Director typically requires a master's degree in computer science, mathematics, engineering or equivalent. Typically reports to top management. The Data Science Director manages a departmental sub-function within a broader departmental function. Creates functional strategies and specific objectives for the sub-function and develops budgets/policies/procedures to support the functional infrastructure. To be a Data Science Director typically requires 5+ years of managerial experience. Deep knowledge of the managed sub-function and solid knowledge of the overall departmental function. (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.