General Summary of Position:
We are seeking a Data Scientist (temporary) to provide data analysis services for real-world clinical research by selecting and applying appropriate analytical methods to answer questions and test hypotheses as specified by clinical researchers, administrators, and clinicians.
Minimum Qualifications (Required):
Education: Master’s Degree in Computer Science, Data Science, Bioinformatics field or related.
Experience: Fluency in programming language (Python, SQL, SOLR)
Skills: Deep understanding of predictive modeling, machine learning, clustering and classification techniques, and algorithms
Level I: Masters degree with some related experience
Level II: Masters degree with 1 year of related experience
Level III: Masters degree with 5+ years of related experience
Sr. Data Scientist: Masters degree with 10+ years of related experience
Additional Considerations:
Ability to work independently and as part of a team
Excellent communication and collaboration skills
Ability to prioritize and coordinate multiple tasks to meet tight deadlines determined by commitments to funding agencies, while complying with administrative requests and requirements
Preferred Qualifications:
Expertise in database study design, statistical methods, algorithms, and result interpretation
Designs research and operational databases, performing statistical analyses, and developing reporting infrastructures
Provides services to domain experts on analytical methods
Interacts with a range of experts in database modeling, advanced analytic processes, as well as clinical and domain experts
Special Instructions to Applicants:
Initial review of applications will begin immediately and continue until the position is filled. However, the position may close when an adequate number of qualified applicants is received.
This is a part-time, temporary, non-unit, non-benefited position.
Please include a resume and cover letter with your application. Names and contact information of three references will be required during the application process.
