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Data Science Specialist

2 months ago

Maywood, Illinois, United States Loyola University Full time
Job Summary

We are seeking a highly skilled Research Assistant Professor to join our team at Loyola University's Center for Health Outcomes and Informatics Research (CHOIR). As a key member of our faculty, you will provide biostatistical support on grant applications, work closely with faculty to develop predictive and prescriptive models, and perform data exploration to drive hypothesis generation and knowledge discovery.

Key Responsibilities
  • Provide biostatistical support on grant applications and research projects
  • Collaborate with faculty to develop predictive and prescriptive models using statistical, machine learning, and data science methods
  • Perform data exploration to drive hypothesis generation and knowledge discovery
  • Support applications for external funding and develop data science methodology in grant proposals
  • Develop algorithms and software for health care analytics
  • Provide data science lectures and workshops for the Health Sciences Division
Requirements
  • Doctorate in Data Science or related field
  • 3-5 years of experience as a biostatistician or data scientist
  • Past experience as co-investigator on federally funded projects
  • Preferred: 6-10 years of experience as a data scientist
Preferred Qualifications
  • Proficiency with statistical packages such as SAS or R
  • Proficiency with high-level programming languages such as Python or Java
  • Proficiency with modern data science tools such as Tensorflow or Keras
  • Excellent written and verbal communication skills
  • Ability to work well in multidisciplinary teams
  • High attention to detail and ability to maintain accuracy and consistency
About CHOIR

CHOIR is a core strategic collaboration between Loyola University Chicago's Health Sciences Division and Loyola University Health System. Our mission is to create a data-driven culture in the service of improved outcomes and health equity. We are committed to educating and engaging clinical faculty, healthcare professionals, and health sciences students in the fundamentals of health outcomes research and data-driven healthcare delivery.