Sr. Applied AI Data Scientist - JCHI - 138985

UC San Diego Health is on a journey to build and mature enterprise applied artificial intelligence capabilities that deliver meaningful, measurable impact at scale across the health system. This work reflects a sustained organizational commitment to developing these capabilities as a core part of how care is delivered and supported. The purpose of UCSDH's applied AI efforts is grounded in the quadruple aim, using AI-enabled technologies to simultaneously expand access to care, improve clinical and operational outcomes, enhance quality and safety, and support a better experience for both patients and care teams. A key focus is leveraging real-time data, predictive, generative, and hybrid models, and increasingly automated interventions to demonstrably achieve impact at scale across the health system.

Central to this strategy is the Mission Control vision, which brings together real-time data and applied AI-driven decision support to provide system-wide insight and action across the care continuum, including population health. This initiative serves both as a delivery layer for targeted point solutions across the health system and as a centralized hub for system-level assessment, prediction, and coordinated action. The supporting technology landscape is intentionally dynamic, with an emphasis on identifying best-fit solutions over time while scaling a cohesive enterprise platform that integrates complementary tools and capabilities.

This position operates within the Jacobs Center for Health Innovation and is integrated into UC San Diego Health Information Services, sharing leadership, data, and infrastructure, while driving translational innovation and supporting enterprise operations at scale.

Position and Team:

UC San Diego Health is seeking a Senior Data Scientist to work within the Joan & Irwin Jacobs Center for Health Innovation (JCHI) on all phases of AI model design and development. The role is responsible for the full model lifecycle, including intake and review, data preparation, model development, evaluation, pre-deployment preparation, deployment, and post-deployment model monitoring and management. This includes applying advanced statistical and machine learning methods, causal inference, and experimental design to ensure models not only predict outcomes but drive measurable impact through real-world interventions.

The position operates within a multidisciplinary environment that includes cloud engineers, product managers, AI/automation engineers, application developers, architects, and enterprise platform teams. The Senior Data Scientist owns technical execution across the model lifecycle while partnering closely with product managers who drive product strategy, prioritization, and stakeholder alignment. The position reports to the JCHI Co-Director, who provides functional leadership for data science and AI initiatives and works across JCHI and Information Services stakeholders to align priorities, capabilities, and delivery.

This is a senior technical role that requires the ability to independently lead complex data science projects, mentor junior team members, and contribute to the strategic direction of the data science program. The role involves close collaboration with clinical and operational stakeholders to identify high-impact use cases, translate clinical questions into data science problems, and deliver AI solutions that create sustained value across the health system. This includes working across diverse data modalities (e.g., structured EHR data, time-series, imaging, and unstructured text) and leveraging state-of-the-art approaches, including predictive, generative, and hybrid models.

What We're Looking For:

The ideal candidate brings deep experience across the full AI model lifecycle in healthcare or complex enterprise environments, with demonstrated ability to independently lead projects from data exploration through production deployment and ongoing monitoring. Experience with healthcare EHR data, particularly Epic, is essential, and candidates should be comfortable working with complex, multimodal clinical datasets to develop models that drive measurable improvements in patient care and health system operations at scale.

Experience developing AI models using traditional machine learning, large language models, and hybrid approaches is strongly desired, including familiarity with cloud-based data science platforms such as AWS and modern ML infrastructure. Candidates should be highly proficient in Python, R, SQL, and related tools, with strong expertise in model evaluation, benchmarking, and performance optimization, as well as applying rigorous methods to ensure robustness, generalizability, and real-world impact.

Successful candidates will also demonstrate strong familiarity with enterprise health system operations and technologies, including electronic health records, healthcare data integration, and cloud platforms, along with the regulatory and privacy considerations unique to healthcare AI. The role requires the ability to work effectively across clinical, operational, technical, and vendor stakeholders, and to contribute to data science strategy in environments where innovation, scientific rigor, and patient safety must coexist.

• Nine (9) years of related experience, education/training, OR a Bachelor's degree in related area plus five (5) years of related experience/training. Related experience includes data science, computational science, machine learning, AI model development, and work with healthcare EHR data (e.g., Epic).

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

• Demonstrated ability to initiate research proposals and acquire funding.

• 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.

• 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.

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

• Strong data science discipline across the full AI model lifecycle (intake, data prep, model development, evaluation, deployment, monitoring).Demonstrated ability to lead complex data science research projects with multi-institutional scope and serve as technical lead.

• Healthcare data science platform experience in AWS, including model training, deployment, and monitoring.

• Advanced proficiency in Python, R, SQL, ML frameworks, data visualization, and big-data/cloud platforms (AWS or Azure).

• Experience developing AI models using traditional ML, LLMs, and hybrid approaches (generative and predictive AI applied to clinical/operational workflows).

• In-depth experience with benchmarking, profiling, and performance analysis of data science code.

• Experience with Epic EHR data and integrating AI solutions with Epic and related clinical data environments.

• Operational familiarity with population health, clinical operations, or care coordination.

• Experience evaluating and integrating vendor-based AI/data science platforms.

• Experience operating within large academic medical centers or integrated delivery systems.

• Demonstrated ability to translate model outputs into actionable clinical or operational interventions, and to support rigorous evaluation through real-world evidence generation, including opportunities for publication and multi-institutional collaboration

• Ability to translate state-of-the-art methods into production-ready solutions within complex, real-world environments

• Experience with causal inference, experimental design, or decision-focused modeling to evaluate and drive real-world interventions

• Experience with prospective validation or study design in clinical or operational environments, including real-world evidence generation

• Experience partnering across data engineering, clinical, operational, and executive stakeholders to define, develop, and sustain data science products in complex healthcare organizations

• Operational familiarity with healthcare domains such as population health, clinical operations, or care coordination

• Must be able to work various hours and locations based on business needs.

• Employment is subject to a criminal background check and pre-employment physical.

If employed by the University of California, you will be required to comply with our Policy on Vaccination Programs, which may be amended or revised from time to time. Federal, state, or local public health directives may impose additional requirements.

If applicable, life-support certifications (BLS, NRP, ACLS, etc.) must include hands-on practice and in-person skills assessment; online-only certification is not acceptable.

UC San Diego Health is the only academic health system in the San Diego region, providing leading-edge care in patient care, biomedical research, education, and community service. Our facilities include two university hospitals, a National Cancer Institute-designated Comprehensive Cancer Center, Shiley Eye Institute, Sulpizio Cardiovascular Center, the only Burn Center in the county, and dozens of outpatient clinics. We invite you to join our team!

Applications/Resumes are accepted for current job openings only. For full consideration on any job, applications must be received prior to the initial closing date. If a job has an extended deadline, applications/resumes will be considered during the extension period; however, a job may be filled before the extended date is reached.

To foster the best possible working and learning environment, UC San Diego strives to cultivate a rich and diverse environment, inclusive and supportive of all students, faculty, staff and visitors. For more information, please visit UC San Diego Principles of Community.

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.

For the University of California's Anti-Discrimination Policy, please visit: https://policy.ucop.edu/doc/1001004/Anti-Discrimination

UC San Diego is a smoke and tobacco free environment. Please visit smokefree.ucsd.edu for more information.

UC San Diego Health maintains a marijuana and drug free environment. Employees may be subject to drug screening.

Misconduct Disclosure Requirement: As a condition of employment, the final candidate who accepts an offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; or have filed an appeal of a finding of substantiated misconduct with a previous employer.

a. "Misconduct" means any violation of the policies governing employee conduct at the applicant's previous place of employment, including, but not limited to, violations of policies prohibiting sexual harassment, sexual assault, or other forms of harassment, or discrimination, as defined by the employer. For reference, below are UC's policies addressing some forms of misconduct:

• UC Sexual Violence and Sexual Harassment Policy
• UC Anti-Discrimination Policy
• Abusive Conduct in the Workplace