Data Scientist - Hybrid - 140926

The Department of Orthopaedic Surgery at UC San Diego School of Medicine is a diverse patient, research, education, and academia focused, high-performing Department with a commitment to quality, collaboration, innovation, and continuous improvement. Orthopaedic Surgery provides treatment for disorders of the musculoskeletal system, offering comprehensive and innovative services. The Department offers a full spectrum of musculoskeletal clinical care, specializing in foot and ankle, hand and microvascular surgery, joint reconstruction, physical medicine and rehabilitation, spine, sports medicine, orthopaedic oncology, and trauma. Research expertise includes advancements in muscle metabolism and physiology, neuromuscular bioengineering, intervertebral disc, and musculoskeletal physiology and epidemiology. The Department supports an ACGME accredited residency program and fellowship in hand and microvascular surgery, as well as fellowship programs in joint reconstruction, spine, and trauma.

Under the general direction of the Principal Investigator (PI), this position provides advanced research, computational, and systems support for spine-focused orthopedic studies. The incumbent leads the design and optimization of data science tools, computational models, and large-scale data infrastructure that enable high-impact research on biologic, physiologic, clinical, and economic health outcomes related to spine conditions. This role applies deep expertise in computer science, data science, and distributed computing to build and maintain complex storage, networking, and high-performance computing (HPC) environments that support multidisciplinary research teams. The position also contributes to major system implementations, resolves advanced technical issues, and may provide guidance to research and technical staff, ensuring the reliability, security, and scalability of critical research systems. Other duties are performed as needed to support ongoing scientific and operational objectives.

Applies advanced computational, computer science, data science, and CI software research and development principles, with relevant domain science knowledge where applicable, to perform highly complex research, technology and software development which involve in-depth evaluation of variable factors impacting medium to large projects of broad scope and complexities. Designs, develops, and optimizes components / tools for major HPC / data science / CI projects in diverse research application areas. Resolves complex research and technology development and integration issues. Gives technical presentations to associated research and technology groups and management. Evaluates new hardware and software technologies for advancing complex HPC, data science, CI projects. May represent the organization as part of a team at national and international meetings, conferences and committees. Assists in the design, implementation and recommends new hardware and software technologies for advancing complex HPC, data science, CI projects. May lead a team of research and technical staff.

• Nine (9) years of related experience, education/training, OR a Bachelor's degree in related area plus five(5)or more years of relevant experience.

• Advanced knowledge of HPC/data science/CI.

• Highly advanced skills, and demonstrated experience associated with one or more of the following: HPC hardware and software power and performance analysis and research, design, modification, implementation and deployment of HPC or data science or CI applications and tools of large-scale scope. Demonstrated knowledge of cloud and highly complex multi-institutional data science and software implementation studies.

• Demonstrated ability to regularly, effectively communicate with unit-level management.

• Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences.

• In depth skills and experience in independently resolving complex computing / data / CI problems using introductory and/or intermediate principles.

• Self-motivated and works independently and as part of a team.

• Advanced experience working in a complex computing/data/CI environment encompassing all or some of the following: HPC, data science infrastructure and tools/software, and diverse domain science application base.

• In depth ability to successfully work and/or lead multiple concurrent projects. Demonstrated research and technology project leadership and management skills. Experience in working with a multi-center team of clinical and hospital IT experts to deploy highly advanced clinical decision support systems involving artificial intelligence.

• In depth experience assessing a broad spectrum of technical and research needs and demands and establish priorities, delegate and/or lead development of solutions to meet such needs.

• Demonstrated advanced experience in one or more of the following: optimizing, benchmarking, HPC performance and power modeling, analyzing hardware, software, and applications for HPC/data /CI.

• Demonstrated advanced experience working with Python, TensorFlow, PyTorch, Matlab. Must have experience with real-time implementation of artificial Intelligence clinical decision support systems and health care data exchange protocols.

• Advanced knowledge of cloud computing environments such as Amazon Web Services (AWS) and Google Cloud platform (GCP), artificial Intelligence system architecture design, and scalable and serverless computing.

• Demonstrated ability to initiate research proposals and acquire funding.

• Demonstrated experience in grant submittals and/or publications.

• Master's degree in Computer/Computational/Data Science, or Domain Sciences with computer/computational/data specialization.

• Five (5) or more years of relevant experience in big data analytics, predictive modeling, artificial intelligence and healthcare.

• Doctorate degree in a related field.

• Experience in multisite clinical data harmonization.

• Demonstrated knowledge of common data fields in the area of musculoskeletal clinical care.

• Employment is subject to a criminal background check.

• Overtime and weekends may be required.