Full TimeDays8 Hours Monday-Friday 8:00am-5:00pmClinical, imaging, and genetic data at scale are powerful tools for biological discovery and risk prediction. Carefully structured analyses and reproducible analytic pipelines accelerate ongoing efforts to gain clinically relevant insights.
Our research efforts are at the intersection of cardiovascular disease and human genetics—including both somatic and germline variation. Our clinical research efforts employ new techniques for deep phenotyping, such as deep learning. But these techniques rely on a solid foundation of classical bioinformatics. The Bioinformatics Programmer/Data Scientist will assist in managing, cleaning, and analyzing large scale medical data using a wide variety of analytic techniques, both in the cloud and with on-premises compute depending on data permissions. Experience with a cloud provider such as AWS or Google Cloud is a plus, and ability to learn how to manage cloud-based pipelines, and to perform cloud data management will be essential to learn. Maintaining bioinformatic databases by obtaining and restructuring data, including both UCSF proprietary data and public data, and writing tools to streamline discovery and replication analyses using these databases will be core responsibilities. An important task will be writing and maintaining analytic pipelines in languages such as R, python, Go, Rust, shell, SQL, WDL, and/or other appropriate languages, and using tools such as Docker. Experience with databases or the ability to learn will be requisite. Under the supervision of the PI, the Data Scientist will also be involved in data analysis, and will be comfortable with bioinformatic analyses including variant calling and annotation. There will be opportunities to employ cutting-edge methods and to develop new methods. The ability to learn and implement new techniques depending on the problem at hand will be an essential skill, thus requiring a strong foundation in computer programming. This position will also include administrative duties and will have the opportunity to participate in—and to lead—authorship teams.

The final salary and offer components are subject to additional approvals based on UC policy.

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Please note: An offer will take into consideration the experience of the final candidate AND the current salary level of individuals working at UCSF in a similar role.

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• Bachelor's degree in biological science, computational / programming, or related area and one or more years of relevant experience and / or equivalent experience / training
• Working knowledge of bioinformatics methods and data structures
• Working knowledge of biostatistics and basic statistical testing
• Working knowledge of systems programming and databases
• Working knowledge of application and data security concepts
• Ability to effectively manage time and see assigned parts of projects through to completion on deadline
• Basic consultation and communication skills
• Demonstrated fluency and competency with statistical programming with the R programming language or the Python programming language
• Experience with or a demonstrated ability to learn and implement data management and computational pipelines for management of large-scale data
• At least 6 months of experience in direct data management and analysis using medical and/or health-related data using the above tools
• Ability to lead and maintain data pipelines for real-time data acquisition from clinical systems
• Ability to multi-task and work well with limited supervision
• Working project management skills
• Interpersonal skills in order to work with both technical and non-technical personnel at various levels in the organization
• Ability to communicate technical information in a clear and concise manner
• Self-motivated, able to learn quickly, meet deadlines and demonstrate problem solving skills

• MS or greater in a related science or an equivalent combination of education and experience
• PhD in a field relevant to biomedical research (bioinformatics, biomedical engineering), or computer science (computer science, machine learning, artificial intelligence) or similar
• 12 months or more of demonstrated work experience using medical and/or health-related data, or similar, including developing pipelines for extracting, transforming, and loading data, and data analysis