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Über
Zuckerberg San Francisco General Hospital and the Division of Cardiology is at the forefront of applying artificial intelligence and machine learning (AI/ML) to help improve outcomes in vulnerable and underserved populations. We currently have a successful and growing ML predictive analytics team consisting of ML researchers, clinicians, informaticists, and biostatisticians. We seek a data scientist to join our team to develop AI/ML-based algorithms to support clinical decision making, hospital performance improvement efforts, and more. This position requires experience in computer science, (bio)statistics, or another relevant field. A proven track record of productivity within academia or industry in publishing and/or developing and applying new algorithms is necessary for this role. The candidate should have experience developing in a Linux environment, using git-based workflows, writing in Python/R, using high-performance computing, and working collaboratively with a multidisclinary team. Ideally, the candidate also has experience cleaning and analyzing Electronic Health Record (EHR) data, creating datawarehouses for data analytics, and experience/interest in developing new ML algorithms including large language models. The final salary and offer components are subject to additional approvals based on UC policy. Your placement within the salary range is dependent on a number of factors including your work experience and internal equity within this position classification at UCSF. For positions that are represented by a labor union, placement within the salary range will be guided by the rules in the collective bargaining agreement. The salary range for this position is $148,700 - $360,900 (Annual Rate). To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.
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- English
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